Overview

Dataset statistics

Number of variables65
Number of observations435
Missing cells7752
Missing cells (%)27.4%
Total size in memory2.7 MiB
Average record size in memory6.3 KiB

Variable types

Numeric1
Text64

Alerts

state_code has constant value ""Constant
se_services has constant value ""Constant
priority08 has constant value ""Constant
priority09 has constant value ""Constant
priority10 has constant value ""Constant
fax_number has 12 (2.8%) missing valuesMissing
expgrade_span_min has 404 (92.9%) missing valuesMissing
expgrade_span_max has 402 (92.4%) missing valuesMissing
subway has 77 (17.7%) missing valuesMissing
website has 5 (1.1%) missing valuesMissing
total_students has 9 (2.1%) missing valuesMissing
campus_name has 218 (50.1%) missing valuesMissing
school_type has 331 (76.1%) missing valuesMissing
language_classes has 23 (5.3%) missing valuesMissing
advancedplacement_courses has 95 (21.8%) missing valuesMissing
online_ap_courses has 371 (85.3%) missing valuesMissing
online_language_courses has 362 (83.2%) missing valuesMissing
psal_sports_boys has 62 (14.3%) missing valuesMissing
psal_sports_girls has 62 (14.3%) missing valuesMissing
psal_sports_coed has 288 (66.2%) missing valuesMissing
school_sports has 138 (31.7%) missing valuesMissing
partner_cbo has 81 (18.6%) missing valuesMissing
partner_hospital has 239 (54.9%) missing valuesMissing
partner_highered has 57 (13.1%) missing valuesMissing
partner_cultural has 130 (29.9%) missing valuesMissing
partner_nonprofit has 138 (31.7%) missing valuesMissing
partner_corporate has 237 (54.5%) missing valuesMissing
partner_financial has 363 (83.4%) missing valuesMissing
partner_other has 247 (56.8%) missing valuesMissing
addtl_info1 has 81 (18.6%) missing valuesMissing
addtl_info2 has 206 (47.4%) missing valuesMissing
priority02 has 83 (19.1%) missing valuesMissing
priority03 has 192 (44.1%) missing valuesMissing
priority04 has 258 (59.3%) missing valuesMissing
priority05 has 396 (91.0%) missing valuesMissing
priority06 has 418 (96.1%) missing valuesMissing
priority07 has 431 (99.1%) missing valuesMissing
priority08 has 434 (99.8%) missing valuesMissing
priority09 has 434 (99.8%) missing valuesMissing
priority10 has 434 (99.8%) missing valuesMissing
0 has unique valuesUnique
dbn has unique valuesUnique
school_name has unique valuesUnique
extracurricular_activities has unique valuesUnique

Reproduction

Analysis started2023-12-09 22:17:04.772338
Analysis finished2023-12-09 22:17:08.437407
Duration3.67 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct435
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218
Minimum1
Maximum435
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-09T22:17:08.580683image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.7
Q1109.5
median218
Q3326.5
95-th percentile413.3
Maximum435
Range434
Interquartile range (IQR)217

Descriptive statistics

Standard deviation125.7179383
Coefficient of variation (CV)0.5766877902
Kurtosis-1.2
Mean218
Median Absolute Deviation (MAD)109
Skewness0
Sum94830
Variance15805
MonotonicityStrictly increasing
2023-12-09T22:17:08.743567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
287 1
 
0.2%
298 1
 
0.2%
297 1
 
0.2%
296 1
 
0.2%
295 1
 
0.2%
294 1
 
0.2%
293 1
 
0.2%
292 1
 
0.2%
291 1
 
0.2%
Other values (425) 425
97.7%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
ValueCountFrequency (%)
435 1
0.2%
434 1
0.2%
433 1
0.2%
432 1
0.2%
431 1
0.2%

dbn
Text

UNIQUE 

Distinct435
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.9 KiB
2023-12-09T22:17:09.196806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2610
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)100.0%

Sample

1st row27Q260
2nd row21K559
3rd row16K393
4th row08X305
5th row03M485
ValueCountFrequency (%)
31r600 1
 
0.2%
30q501 1
 
0.2%
13k499 1
 
0.2%
07x223 1
 
0.2%
20k505 1
 
0.2%
02m500 1
 
0.2%
29q283 1
 
0.2%
13k350 1
 
0.2%
30q301 1
 
0.2%
02m316 1
 
0.2%
Other values (425) 425
97.7%
2023-12-09T22:17:09.768604image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 346
13.3%
0 329
12.6%
1 268
10.3%
4 250
9.6%
5 246
9.4%
3 200
7.7%
6 152
 
5.8%
9 139
 
5.3%
8 124
 
4.8%
7 121
 
4.6%
Other values (5) 435
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2175
83.3%
Uppercase Letter 435
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 346
15.9%
0 329
15.1%
1 268
12.3%
4 250
11.5%
5 246
11.3%
3 200
9.2%
6 152
7.0%
9 139
6.4%
8 124
 
5.7%
7 121
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
K 121
27.8%
X 118
27.1%
M 106
24.4%
Q 80
18.4%
R 10
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2175
83.3%
Latin 435
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 346
15.9%
0 329
15.1%
1 268
12.3%
4 250
11.5%
5 246
11.3%
3 200
9.2%
6 152
7.0%
9 139
6.4%
8 124
 
5.7%
7 121
 
5.6%
Latin
ValueCountFrequency (%)
K 121
27.8%
X 118
27.1%
M 106
24.4%
Q 80
18.4%
R 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 346
13.3%
0 329
12.6%
1 268
10.3%
4 250
9.6%
5 246
9.4%
3 200
7.7%
6 152
 
5.8%
9 139
 
5.3%
8 124
 
4.8%
7 121
 
4.6%
Other values (5) 435
16.7%

school_name
Text

UNIQUE 

Distinct435
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
2023-12-09T22:17:10.149374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length58
Mean length36.91954023
Min length11

Characters and Unicode

Total characters16060
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)100.0%

Sample

1st rowFrederick Douglass Academy VI High School
2nd rowLife Academy High School for Film and Music
3rd rowFrederick Douglass Academy IV Secondary School
4th rowPablo Neruda Academy
5th rowFiorello H. LaGuardia High School of Music & Art and Performing Arts
ValueCountFrequency (%)
school 340
 
14.3%
high 230
 
9.7%
for 136
 
5.7%
academy 101
 
4.2%
and 96
 
4.0%
the 57
 
2.4%
of 55
 
2.3%
college 37
 
1.6%
bronx 37
 
1.6%
arts 37
 
1.6%
Other values (506) 1254
52.7%
2023-12-09T22:17:10.716565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1945
 
12.1%
o 1502
 
9.4%
e 1113
 
6.9%
a 916
 
5.7%
n 837
 
5.2%
i 829
 
5.2%
r 828
 
5.2%
l 815
 
5.1%
h 806
 
5.0%
c 757
 
4.7%
Other values (61) 5712
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11687
72.8%
Uppercase Letter 2271
 
14.1%
Space Separator 1945
 
12.1%
Other Punctuation 121
 
0.8%
Decimal Number 17
 
0.1%
Dash Punctuation 7
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1502
12.9%
e 1113
9.5%
a 916
 
7.8%
n 837
 
7.2%
i 829
 
7.1%
r 828
 
7.1%
l 815
 
7.0%
h 806
 
6.9%
c 757
 
6.5%
t 554
 
4.7%
Other values (16) 2730
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 479
21.1%
H 308
13.6%
A 236
10.4%
C 176
 
7.7%
T 119
 
5.2%
B 110
 
4.8%
E 104
 
4.6%
M 96
 
4.2%
L 88
 
3.9%
P 81
 
3.6%
Other values (16) 474
20.9%
Decimal Number
ValueCountFrequency (%)
2 4
23.5%
3 3
17.6%
6 2
11.8%
4 2
11.8%
7 2
11.8%
1 2
11.8%
8 1
 
5.9%
0 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 42
34.7%
, 38
31.4%
: 16
 
13.2%
& 15
 
12.4%
' 6
 
5.0%
/ 4
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 5
71.4%
– 2
 
28.6%
Space Separator
ValueCountFrequency (%)
1945
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13958
86.9%
Common 2102
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1502
 
10.8%
e 1113
 
8.0%
a 916
 
6.6%
n 837
 
6.0%
i 829
 
5.9%
r 828
 
5.9%
l 815
 
5.8%
h 806
 
5.8%
c 757
 
5.4%
t 554
 
4.0%
Other values (42) 5001
35.8%
Common
ValueCountFrequency (%)
1945
92.5%
. 42
 
2.0%
, 38
 
1.8%
: 16
 
0.8%
& 15
 
0.7%
( 6
 
0.3%
' 6
 
0.3%
) 6
 
0.3%
- 5
 
0.2%
2 4
 
0.2%
Other values (9) 19
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16058
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1945
 
12.1%
o 1502
 
9.4%
e 1113
 
6.9%
a 916
 
5.7%
n 837
 
5.2%
i 829
 
5.2%
r 828
 
5.2%
l 815
 
5.1%
h 806
 
5.0%
c 757
 
4.7%
Other values (60) 5710
35.6%
Punctuation
ValueCountFrequency (%)
– 2
100.0%

boro
Text

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
2023-12-09T22:17:10.901979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length7.177011494
Min length5

Characters and Unicode

Total characters3122
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowQueens
2nd rowBrooklyn
3rd rowBrooklyn
4th rowBronx
5th rowManhattan
ValueCountFrequency (%)
brooklyn 121
27.2%
bronx 118
26.5%
manhattan 106
23.8%
queens 80
18.0%
staten 10
 
2.2%
island 10
 
2.2%
2023-12-09T22:17:11.206739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 551
17.6%
o 360
11.5%
a 338
10.8%
B 239
 
7.7%
r 239
 
7.7%
t 232
 
7.4%
e 170
 
5.4%
l 131
 
4.2%
k 121
 
3.9%
y 121
 
3.9%
Other values (10) 620
19.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2667
85.4%
Uppercase Letter 445
 
14.3%
Space Separator 10
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 551
20.7%
o 360
13.5%
a 338
12.7%
r 239
9.0%
t 232
8.7%
e 170
 
6.4%
l 131
 
4.9%
k 121
 
4.5%
y 121
 
4.5%
x 118
 
4.4%
Other values (4) 286
10.7%
Uppercase Letter
ValueCountFrequency (%)
B 239
53.7%
M 106
23.8%
Q 80
 
18.0%
S 10
 
2.2%
I 10
 
2.2%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3112
99.7%
Common 10
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 551
17.7%
o 360
11.6%
a 338
10.9%
B 239
 
7.7%
r 239
 
7.7%
t 232
 
7.5%
e 170
 
5.5%
l 131
 
4.2%
k 121
 
3.9%
y 121
 
3.9%
Other values (9) 610
19.6%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 551
17.6%
o 360
11.5%
a 338
10.8%
B 239
 
7.7%
r 239
 
7.7%
t 232
 
7.4%
e 170
 
5.4%
l 131
 
4.2%
k 121
 
3.9%
y 121
 
3.9%
Other values (10) 620
19.9%

building_code
Text

Distinct256
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size26.0 KiB
2023-12-09T22:17:11.715967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1740
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)40.2%

Sample

1st rowQ465
2nd rowK400
3rd rowK026
4th rowX450
5th rowM485
ValueCountFrequency (%)
x425 6
 
1.4%
x410 6
 
1.4%
x450 6
 
1.4%
x435 6
 
1.4%
m490 6
 
1.4%
x405 6
 
1.4%
x415 5
 
1.1%
m445 5
 
1.1%
k400 5
 
1.1%
k465 5
 
1.1%
Other values (246) 379
87.1%
2023-12-09T22:17:12.357499image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 271
15.6%
0 257
14.8%
5 200
11.5%
K 121
 
7.0%
X 118
 
6.8%
M 106
 
6.1%
6 103
 
5.9%
2 90
 
5.2%
1 83
 
4.8%
Q 80
 
4.6%
Other values (5) 311
17.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1305
75.0%
Uppercase Letter 435
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 271
20.8%
0 257
19.7%
5 200
15.3%
6 103
 
7.9%
2 90
 
6.9%
1 83
 
6.4%
3 79
 
6.1%
7 78
 
6.0%
8 78
 
6.0%
9 66
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
K 121
27.8%
X 118
27.1%
M 106
24.4%
Q 80
18.4%
R 10
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1305
75.0%
Latin 435
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 271
20.8%
0 257
19.7%
5 200
15.3%
6 103
 
7.9%
2 90
 
6.9%
1 83
 
6.4%
3 79
 
6.1%
7 78
 
6.0%
8 78
 
6.0%
9 66
 
5.1%
Latin
ValueCountFrequency (%)
K 121
27.8%
X 118
27.1%
M 106
24.4%
Q 80
18.4%
R 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 271
15.6%
0 257
14.8%
5 200
11.5%
K 121
 
7.0%
X 118
 
6.8%
M 106
 
6.1%
6 103
 
5.9%
2 90
 
5.2%
1 83
 
4.8%
Q 80
 
4.6%
Other values (5) 311
17.9%

phone_number
Text

Distinct427
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size29.4 KiB
2023-12-09T22:17:12.689511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.0137931
Min length12

Characters and Unicode

Total characters5226
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)97.0%

Sample

1st row718-471-2154
2nd row718-333-7750
3rd row718-574-2820
4th row718-824-1682
5th row212-496-0700
ValueCountFrequency (%)
718-381-7100 4
 
0.9%
212-927-1841 3
 
0.7%
718-387-2800 2
 
0.5%
718-410-4242 2
 
0.5%
718-904-4200 2
 
0.5%
212-757-5274 1
 
0.2%
718-410-3430 1
 
0.2%
718-696-3820 1
 
0.2%
212-225-0998 1
 
0.2%
212-501-3318 1
 
0.2%
Other values (417) 417
95.9%
2023-12-09T22:17:13.163048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 870
16.6%
1 711
13.6%
8 616
11.8%
7 595
11.4%
2 541
10.4%
0 444
8.5%
3 332
 
6.4%
4 296
 
5.7%
6 291
 
5.6%
5 273
 
5.2%
Other values (2) 257
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4350
83.2%
Dash Punctuation 870
 
16.6%
Space Separator 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 711
16.3%
8 616
14.2%
7 595
13.7%
2 541
12.4%
0 444
10.2%
3 332
7.6%
4 296
6.8%
6 291
6.7%
5 273
 
6.3%
9 251
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 870
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5226
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 870
16.6%
1 711
13.6%
8 616
11.8%
7 595
11.4%
2 541
10.4%
0 444
8.5%
3 332
 
6.4%
4 296
 
5.7%
6 291
 
5.6%
5 273
 
5.2%
Other values (2) 257
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 870
16.6%
1 711
13.6%
8 616
11.8%
7 595
11.4%
2 541
10.4%
0 444
8.5%
3 332
 
6.4%
4 296
 
5.7%
6 291
 
5.6%
5 273
 
5.2%
Other values (2) 257
 
4.9%

fax_number
Text

MISSING 

Distinct422
Distinct (%)99.8%
Missing12
Missing (%)2.8%
Memory size29.0 KiB
2023-12-09T22:17:13.465478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5076
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique421 ?
Unique (%)99.5%

Sample

1st row718-471-2890
2nd row718-333-7775
3rd row718-574-2821
4th row718-824-1663
5th row212-724-5748
ValueCountFrequency (%)
212-674-8021 2
 
0.5%
212-501-1195 1
 
0.2%
718-542-0841 1
 
0.2%
718-564-2567 1
 
0.2%
917-441-3693 1
 
0.2%
718-525-6276 1
 
0.2%
718-927-0411 1
 
0.2%
718-815-9638 1
 
0.2%
718-946-5035 1
 
0.2%
718-387-2748 1
 
0.2%
Other values (412) 412
97.4%
2023-12-09T22:17:13.874806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 846
16.7%
1 678
13.4%
7 622
12.3%
8 611
12.0%
2 557
11.0%
6 323
 
6.4%
3 323
 
6.4%
5 306
 
6.0%
9 303
 
6.0%
4 283
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4230
83.3%
Dash Punctuation 846
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 678
16.0%
7 622
14.7%
8 611
14.4%
2 557
13.2%
6 323
7.6%
3 323
7.6%
5 306
7.2%
9 303
7.2%
4 283
6.7%
0 224
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 846
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5076
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 846
16.7%
1 678
13.4%
7 622
12.3%
8 611
12.0%
2 557
11.0%
6 323
 
6.4%
3 323
 
6.4%
5 306
 
6.0%
9 303
 
6.0%
4 283
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5076
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 846
16.7%
1 678
13.4%
7 622
12.3%
8 611
12.0%
2 557
11.0%
6 323
 
6.4%
3 323
 
6.4%
5 306
 
6.0%
9 303
 
6.0%
4 283
 
5.6%

grade_span_min
Text

Distinct3
Distinct (%)0.7%
Missing3
Missing (%)0.7%
Memory size24.7 KiB
2023-12-09T22:17:13.997831image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters432
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row9
ValueCountFrequency (%)
9 351
81.2%
6 79
 
18.3%
7 2
 
0.5%
2023-12-09T22:17:14.221917image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 351
81.2%
6 79
 
18.3%
7 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 432
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 351
81.2%
6 79
 
18.3%
7 2
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 351
81.2%
6 79
 
18.3%
7 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 351
81.2%
6 79
 
18.3%
7 2
 
0.5%

grade_span_max
Text

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2023-12-09T22:17:14.344161image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.993103448
Min length1

Characters and Unicode

Total characters867
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12
ValueCountFrequency (%)
12 404
92.9%
11 19
 
4.4%
10 9
 
2.1%
9 3
 
0.7%
2023-12-09T22:17:14.586964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 451
52.0%
2 404
46.6%
0 9
 
1.0%
9 3
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 867
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 451
52.0%
2 404
46.6%
0 9
 
1.0%
9 3
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 867
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 451
52.0%
2 404
46.6%
0 9
 
1.0%
9 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 451
52.0%
2 404
46.6%
0 9
 
1.0%
9 3
 
0.3%

expgrade_span_min
Text

MISSING 

Distinct2
Distinct (%)6.5%
Missing404
Missing (%)92.9%
Memory size14.5 KiB
2023-12-09T22:17:14.718546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters31
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row6
ValueCountFrequency (%)
9 26
83.9%
6 5
 
16.1%
2023-12-09T22:17:14.984927image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 26
83.9%
6 5
 
16.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 26
83.9%
6 5
 
16.1%

Most occurring scripts

ValueCountFrequency (%)
Common 31
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 26
83.9%
6 5
 
16.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 26
83.9%
6 5
 
16.1%

expgrade_span_max
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing402
Missing (%)92.4%
Memory size14.6 KiB
2023-12-09T22:17:15.152020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters66
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row14
2nd row12
3rd row12
4th row14
5th row12
ValueCountFrequency (%)
12 27
81.8%
14 6
 
18.2%
2023-12-09T22:17:15.437495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 33
50.0%
2 27
40.9%
4 6
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 33
50.0%
2 27
40.9%
4 6
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 66
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 33
50.0%
2 27
40.9%
4 6
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 33
50.0%
2 27
40.9%
4 6
 
9.1%

bus
Text

Distinct235
Distinct (%)54.1%
Missing1
Missing (%)0.2%
Memory size40.3 KiB
2023-12-09T22:17:16.060870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length141
Median length63
Mean length37.79723502
Min length3

Characters and Unicode

Total characters16404
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)33.9%

Sample

1st rowQ113, Q22
2nd rowB1, B3, B4, B6, B64, B82
3rd rowB15, B38, B46, B47, B52, B54, Q24
4th rowBx22, Bx27, Bx36, Bx39, Bx5
5th rowM10, M104, M11, M20, M31, M5, M57, M66, M7, M72
ValueCountFrequency (%)
m5 50
 
1.6%
bx15 49
 
1.5%
m15 46
 
1.4%
bx41 46
 
1.4%
bx17 45
 
1.4%
bx1 45
 
1.4%
m7 45
 
1.4%
m101 45
 
1.4%
bx2 42
 
1.3%
bx19 42
 
1.3%
Other values (226) 2770
85.9%
2023-12-09T22:17:16.838641image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2793
17.0%
, 2786
17.0%
B 1819
11.1%
1 1339
8.2%
x 925
 
5.6%
M 860
 
5.2%
2 802
 
4.9%
4 797
 
4.9%
3 657
 
4.0%
Q 597
 
3.6%
Other values (19) 3029
18.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6060
36.9%
Uppercase Letter 3710
22.6%
Space Separator 2793
17.0%
Other Punctuation 2786
17.0%
Lowercase Letter 940
 
5.7%
Dash Punctuation 115
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1339
22.1%
2 802
13.2%
4 797
13.2%
3 657
10.8%
5 560
9.2%
6 522
 
8.6%
0 493
 
8.1%
7 368
 
6.1%
8 280
 
4.6%
9 242
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
x 925
98.4%
t 5
 
0.5%
a 2
 
0.2%
n 2
 
0.2%
o 1
 
0.1%
l 1
 
0.1%
i 1
 
0.1%
c 1
 
0.1%
d 1
 
0.1%
h 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
B 1819
49.0%
M 860
23.2%
Q 597
 
16.1%
S 300
 
8.1%
A 104
 
2.8%
D 30
 
0.8%
Space Separator
ValueCountFrequency (%)
2793
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2786
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11754
71.7%
Latin 4650
 
28.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 1819
39.1%
x 925
19.9%
M 860
18.5%
Q 597
 
12.8%
S 300
 
6.5%
A 104
 
2.2%
D 30
 
0.6%
t 5
 
0.1%
a 2
 
< 0.1%
n 2
 
< 0.1%
Other values (6) 6
 
0.1%
Common
ValueCountFrequency (%)
2793
23.8%
, 2786
23.7%
1 1339
11.4%
2 802
 
6.8%
4 797
 
6.8%
3 657
 
5.6%
5 560
 
4.8%
6 522
 
4.4%
0 493
 
4.2%
7 368
 
3.1%
Other values (3) 637
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16404
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2793
17.0%
, 2786
17.0%
B 1819
11.1%
1 1339
8.2%
x 925
 
5.6%
M 860
 
5.2%
2 802
 
4.9%
4 797
 
4.9%
3 657
 
4.0%
Q 597
 
3.6%
Other values (19) 3029
18.5%

subway
Text

MISSING 

Distinct186
Distinct (%)52.0%
Missing77
Missing (%)17.7%
Memory size40.0 KiB
2023-12-09T22:17:17.092593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length218
Median length111
Mean length50.21787709
Min length12

Characters and Unicode

Total characters17978
Distinct characters68
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)31.3%

Sample

1st rowA to Beach 25th St-Wavecrest
2nd rowD to 25th Ave ; N to Ave U ; N to Gravesend - 86th St
3rd rowJ to Kosciusko St ; M, Z to Myrtle Ave
4th row1 to 66th St - Lincoln Center ; 2, 3 to 72nd St ; A, B, C, D to 59th St-Columbus Circle
5th rowB, D to Grand St ; F, J, M, Z to Delancey St-Essex St
ValueCountFrequency (%)
to 743
 
16.0%
486
 
10.5%
st 328
 
7.1%
ave 198
 
4.3%
2 126
 
2.7%
5 113
 
2.4%
b 106
 
2.3%
d 91
 
2.0%
c 88
 
1.9%
a 87
 
1.9%
Other values (302) 2279
49.1%
2023-12-09T22:17:17.528985image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4287
23.8%
t 1779
 
9.9%
o 1150
 
6.4%
, 828
 
4.6%
e 793
 
4.4%
a 560
 
3.1%
r 560
 
3.1%
S 550
 
3.1%
n 466
 
2.6%
h 399
 
2.2%
Other values (58) 6606
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8130
45.2%
Space Separator 4287
23.8%
Uppercase Letter 2700
 
15.0%
Decimal Number 1360
 
7.6%
Other Punctuation 1230
 
6.8%
Dash Punctuation 271
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 550
20.4%
A 334
12.4%
B 219
 
8.1%
C 212
 
7.9%
M 128
 
4.7%
R 123
 
4.6%
D 118
 
4.4%
F 116
 
4.3%
G 104
 
3.9%
L 97
 
3.6%
Other values (16) 699
25.9%
Lowercase Letter
ValueCountFrequency (%)
t 1779
21.9%
o 1150
14.1%
e 793
9.8%
a 560
 
6.9%
r 560
 
6.9%
n 466
 
5.7%
h 399
 
4.9%
l 340
 
4.2%
s 272
 
3.3%
v 270
 
3.3%
Other values (15) 1541
19.0%
Decimal Number
ValueCountFrequency (%)
1 252
18.5%
2 203
14.9%
5 189
13.9%
4 183
13.5%
3 166
12.2%
6 138
10.1%
7 71
 
5.2%
9 62
 
4.6%
8 50
 
3.7%
0 46
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 828
67.3%
; 385
31.3%
& 11
 
0.9%
/ 3
 
0.2%
' 3
 
0.2%
Space Separator
ValueCountFrequency (%)
4287
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 271
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10830
60.2%
Common 7148
39.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1779
16.4%
o 1150
 
10.6%
e 793
 
7.3%
a 560
 
5.2%
r 560
 
5.2%
S 550
 
5.1%
n 466
 
4.3%
h 399
 
3.7%
l 340
 
3.1%
A 334
 
3.1%
Other values (41) 3899
36.0%
Common
ValueCountFrequency (%)
4287
60.0%
, 828
 
11.6%
; 385
 
5.4%
- 271
 
3.8%
1 252
 
3.5%
2 203
 
2.8%
5 189
 
2.6%
4 183
 
2.6%
3 166
 
2.3%
6 138
 
1.9%
Other values (7) 246
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17978
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4287
23.8%
t 1779
 
9.9%
o 1150
 
6.4%
, 828
 
4.6%
e 793
 
4.4%
a 560
 
3.1%
r 560
 
3.1%
S 550
 
3.1%
n 466
 
2.6%
h 399
 
2.2%
Other values (58) 6606
36.7%

primary_address_line_1
Text

Distinct258
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
2023-12-09T22:17:17.952045image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length26
Mean length18.92643678
Min length11

Characters and Unicode

Total characters8233
Distinct characters60
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)40.7%

Sample

1st row8-21 Bay 25 Street
2nd row2630 Benson Avenue
3rd row1014 Lafayette Avenue
4th row1980 Lafayette Avenue
5th row100 Amsterdam Avenue
ValueCountFrequency (%)
avenue 187
 
12.9%
street 163
 
11.2%
east 55
 
3.8%
west 47
 
3.2%
road 27
 
1.9%
boulevard 13
 
0.9%
place 10
 
0.7%
350 9
 
0.6%
irving 9
 
0.6%
100 9
 
0.6%
Other values (454) 926
63.6%
2023-12-09T22:17:18.553945image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1020
 
12.4%
e 973
 
11.8%
t 577
 
7.0%
n 403
 
4.9%
0 351
 
4.3%
r 348
 
4.2%
1 336
 
4.1%
a 326
 
4.0%
u 249
 
3.0%
o 239
 
2.9%
Other values (50) 3411
41.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4398
53.4%
Decimal Number 1788
21.7%
Space Separator 1020
 
12.4%
Uppercase Letter 933
 
11.3%
Dash Punctuation 83
 
1.0%
Other Punctuation 11
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 973
22.1%
t 577
13.1%
n 403
9.2%
r 348
 
7.9%
a 326
 
7.4%
u 249
 
5.7%
o 239
 
5.4%
v 237
 
5.4%
s 220
 
5.0%
l 136
 
3.1%
Other values (13) 690
15.7%
Uppercase Letter
ValueCountFrequency (%)
A 220
23.6%
S 191
20.5%
B 66
 
7.1%
E 64
 
6.9%
T 55
 
5.9%
W 55
 
5.9%
R 46
 
4.9%
P 36
 
3.9%
G 28
 
3.0%
F 25
 
2.7%
Other values (13) 147
15.8%
Decimal Number
ValueCountFrequency (%)
0 351
19.6%
1 336
18.8%
2 206
11.5%
5 200
11.2%
3 162
9.1%
4 148
8.3%
9 100
 
5.6%
6 99
 
5.5%
7 97
 
5.4%
8 89
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 10
90.9%
' 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1020
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5331
64.8%
Common 2902
35.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 973
18.3%
t 577
 
10.8%
n 403
 
7.6%
r 348
 
6.5%
a 326
 
6.1%
u 249
 
4.7%
o 239
 
4.5%
v 237
 
4.4%
s 220
 
4.1%
A 220
 
4.1%
Other values (36) 1539
28.9%
Common
ValueCountFrequency (%)
1020
35.1%
0 351
 
12.1%
1 336
 
11.6%
2 206
 
7.1%
5 200
 
6.9%
3 162
 
5.6%
4 148
 
5.1%
9 100
 
3.4%
6 99
 
3.4%
7 97
 
3.3%
Other values (4) 183
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8233
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1020
 
12.4%
e 973
 
11.8%
t 577
 
7.0%
n 403
 
4.9%
0 351
 
4.3%
r 348
 
4.2%
1 336
 
4.1%
a 326
 
4.0%
u 249
 
3.0%
o 239
 
2.9%
Other values (50) 3411
41.4%

city
Text

Distinct28
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
2023-12-09T22:17:18.797257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length8
Mean length7.875862069
Min length5

Characters and Unicode

Total characters3426
Distinct characters43
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.3%

Sample

1st rowFar Rockaway
2nd rowBrooklyn
3rd rowBrooklyn
4th rowBronx
5th rowNew York
ValueCountFrequency (%)
brooklyn 121
20.0%
bronx 118
19.5%
new 104
17.2%
york 104
17.2%
island 22
 
3.6%
jamaica 13
 
2.2%
long 12
 
2.0%
city 12
 
2.0%
staten 10
 
1.7%
flushing 8
 
1.3%
Other values (28) 80
13.2%
2023-12-09T22:17:19.172117image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 507
14.8%
r 385
 
11.2%
n 316
 
9.2%
B 241
 
7.0%
k 240
 
7.0%
l 180
 
5.3%
169
 
4.9%
e 152
 
4.4%
y 141
 
4.1%
a 131
 
3.8%
Other values (33) 964
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2653
77.4%
Uppercase Letter 604
 
17.6%
Space Separator 169
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 507
19.1%
r 385
14.5%
n 316
11.9%
k 240
9.0%
l 180
 
6.8%
e 152
 
5.7%
y 141
 
5.3%
a 131
 
4.9%
x 118
 
4.4%
w 115
 
4.3%
Other values (13) 368
13.9%
Uppercase Letter
ValueCountFrequency (%)
B 241
39.9%
N 104
17.2%
Y 104
17.2%
I 22
 
3.6%
F 17
 
2.8%
C 17
 
2.8%
S 16
 
2.6%
J 13
 
2.2%
L 12
 
2.0%
H 10
 
1.7%
Other values (9) 48
 
7.9%
Space Separator
ValueCountFrequency (%)
169
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3257
95.1%
Common 169
 
4.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 507
15.6%
r 385
11.8%
n 316
 
9.7%
B 241
 
7.4%
k 240
 
7.4%
l 180
 
5.5%
e 152
 
4.7%
y 141
 
4.3%
a 131
 
4.0%
x 118
 
3.6%
Other values (32) 846
26.0%
Common
ValueCountFrequency (%)
169
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 507
14.8%
r 385
 
11.2%
n 316
 
9.2%
B 241
 
7.0%
k 240
 
7.0%
l 180
 
5.3%
169
 
4.9%
e 152
 
4.4%
y 141
 
4.1%
a 131
 
3.8%
Other values (33) 964
28.1%

state_code
Text

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2023-12-09T22:17:19.285432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters870
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNY
2nd rowNY
3rd rowNY
4th rowNY
5th rowNY
ValueCountFrequency (%)
ny 435
100.0%
2023-12-09T22:17:19.502511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 435
50.0%
Y 435
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 870
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 435
50.0%
Y 435
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 870
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 435
50.0%
Y 435
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 870
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 435
50.0%
Y 435
50.0%

zip
Text

Distinct120
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size26.5 KiB
2023-12-09T22:17:19.897835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2175
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)9.2%

Sample

1st row11691
2nd row11214
3rd row11221
4th row10473
5th row10023
ValueCountFrequency (%)
10457 13
 
3.0%
10002 12
 
2.8%
11101 12
 
2.8%
11201 11
 
2.5%
10456 11
 
2.5%
10468 10
 
2.3%
10019 10
 
2.3%
10451 9
 
2.1%
10011 9
 
2.1%
11208 9
 
2.1%
Other values (110) 329
75.6%
2023-12-09T22:17:20.423442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 806
37.1%
0 456
21.0%
2 213
 
9.8%
4 190
 
8.7%
3 151
 
6.9%
6 115
 
5.3%
5 99
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2175
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 806
37.1%
0 456
21.0%
2 213
 
9.8%
4 190
 
8.7%
3 151
 
6.9%
6 115
 
5.3%
5 99
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 806
37.1%
0 456
21.0%
2 213
 
9.8%
4 190
 
8.7%
3 151
 
6.9%
6 115
 
5.3%
5 99
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 806
37.1%
0 456
21.0%
2 213
 
9.8%
4 190
 
8.7%
3 151
 
6.9%
6 115
 
5.3%
5 99
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%

website
Text

MISSING 

Distinct427
Distinct (%)99.3%
Missing5
Missing (%)1.1%
Memory size35.2 KiB
2023-12-09T22:17:20.706794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length80
Median length35
Mean length26.25348837
Min length11

Characters and Unicode

Total characters11289
Distinct characters66
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)98.6%

Sample

1st rowhttp://schools.nyc.gov/schoolportals/27/Q260
2nd rowhttp://schools.nyc.gov/schoolportals/21/K559
3rd rowhttp://schools.nyc.gov/schoolportals/16/K393
4th rowwww.pablonerudaacademy.org
5th rowwww.laguardiahs.org
ValueCountFrequency (%)
www.bard.edu/bhsec 2
 
0.5%
epicschoolsnyc.org 2
 
0.5%
www.ywlnetwork.org 2
 
0.5%
www.ihsph.org 1
 
0.2%
thehssm.com 1
 
0.2%
www.thesls.net 1
 
0.2%
http://schools.nyc.gov/schoolportals/02/m545 1
 
0.2%
www.leadersschool.net 1
 
0.2%
www.validusprep.org 1
 
0.2%
www.sljhs.org 1
 
0.2%
Other values (418) 418
97.0%
2023-12-09T22:17:21.155489image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1223
 
10.8%
w 929
 
8.2%
. 842
 
7.5%
s 786
 
7.0%
c 629
 
5.6%
h 620
 
5.5%
/ 599
 
5.3%
t 570
 
5.0%
r 557
 
4.9%
l 530
 
4.7%
Other values (56) 4004
35.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8911
78.9%
Other Punctuation 1570
 
13.9%
Decimal Number 578
 
5.1%
Uppercase Letter 220
 
1.9%
Dash Punctuation 7
 
0.1%
Connector Punctuation 2
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1223
13.7%
w 929
10.4%
s 786
 
8.8%
c 629
 
7.1%
h 620
 
7.0%
t 570
 
6.4%
r 557
 
6.3%
l 530
 
5.9%
a 425
 
4.8%
g 424
 
4.8%
Other values (16) 2218
24.9%
Uppercase Letter
ValueCountFrequency (%)
X 37
16.8%
M 35
15.9%
K 32
14.5%
S 21
9.5%
Q 14
 
6.4%
H 14
 
6.4%
A 8
 
3.6%
B 7
 
3.2%
C 6
 
2.7%
L 6
 
2.7%
Other values (14) 40
18.2%
Decimal Number
ValueCountFrequency (%)
2 87
15.1%
0 85
14.7%
1 70
12.1%
5 63
10.9%
3 61
10.6%
4 60
10.4%
9 47
8.1%
6 39
6.7%
8 34
 
5.9%
7 32
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 842
53.6%
/ 599
38.2%
: 129
 
8.2%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9131
80.9%
Common 2158
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1223
13.4%
w 929
 
10.2%
s 786
 
8.6%
c 629
 
6.9%
h 620
 
6.8%
t 570
 
6.2%
r 557
 
6.1%
l 530
 
5.8%
a 425
 
4.7%
g 424
 
4.6%
Other values (40) 2438
26.7%
Common
ValueCountFrequency (%)
. 842
39.0%
/ 599
27.8%
: 129
 
6.0%
2 87
 
4.0%
0 85
 
3.9%
1 70
 
3.2%
5 63
 
2.9%
3 61
 
2.8%
4 60
 
2.8%
9 47
 
2.2%
Other values (6) 115
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11289
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1223
 
10.8%
w 929
 
8.2%
. 842
 
7.5%
s 786
 
7.0%
c 629
 
5.6%
h 620
 
5.5%
/ 599
 
5.3%
t 570
 
5.0%
r 557
 
4.9%
l 530
 
4.7%
Other values (56) 4004
35.5%

total_students
Text

MISSING 

Distinct325
Distinct (%)76.3%
Missing9
Missing (%)2.1%
Memory size25.4 KiB
2023-12-09T22:17:21.650596image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.122065728
Min length2

Characters and Unicode

Total characters1330
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique255 ?
Unique (%)59.9%

Sample

1st row412
2nd row260
3rd row155
4th row335
5th row2730
ValueCountFrequency (%)
401 5
 
1.2%
420 4
 
0.9%
345 4
 
0.9%
309 4
 
0.9%
313 4
 
0.9%
439 4
 
0.9%
513 4
 
0.9%
387 4
 
0.9%
416 3
 
0.7%
443 3
 
0.7%
Other values (315) 387
90.8%
2023-12-09T22:17:22.293739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 206
15.5%
4 183
13.8%
1 170
12.8%
5 154
11.6%
2 142
10.7%
6 122
9.2%
7 96
7.2%
9 94
7.1%
0 93
7.0%
8 70
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1330
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 206
15.5%
4 183
13.8%
1 170
12.8%
5 154
11.6%
2 142
10.7%
6 122
9.2%
7 96
7.2%
9 94
7.1%
0 93
7.0%
8 70
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1330
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 206
15.5%
4 183
13.8%
1 170
12.8%
5 154
11.6%
2 142
10.7%
6 122
9.2%
7 96
7.2%
9 94
7.1%
0 93
7.0%
8 70
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1330
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 206
15.5%
4 183
13.8%
1 170
12.8%
5 154
11.6%
2 142
10.7%
6 122
9.2%
7 96
7.2%
9 94
7.1%
0 93
7.0%
8 70
 
5.3%

campus_name
Text

MISSING 

Distinct65
Distinct (%)30.0%
Missing218
Missing (%)50.1%
Memory size25.9 KiB
2023-12-09T22:17:22.669517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length36
Mean length32.1797235
Min length19

Characters and Unicode

Total characters6983
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)3.2%

Sample

1st rowFar Rockaway Educational Campus
2nd rowLafayette Educational Campus
3rd rowAdlai E. Stevenson Educational Campus
4th rowSeward Park Educational Campus
5th rowChristopher Columbus Educational Campus
ValueCountFrequency (%)
campus 218
24.9%
educational 212
24.2%
george 10
 
1.1%
park 10
 
1.1%
washington 9
 
1.0%
john 8
 
0.9%
e 8
 
0.9%
thomas 7
 
0.8%
martin 6
 
0.7%
lehman 6
 
0.7%
Other values (113) 383
43.7%
2023-12-09T22:17:23.181520image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 879
 
12.6%
660
 
9.5%
u 498
 
7.1%
n 405
 
5.8%
o 375
 
5.4%
t 359
 
5.1%
i 352
 
5.0%
s 345
 
4.9%
l 308
 
4.4%
d 299
 
4.3%
Other values (39) 2503
35.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5393
77.2%
Uppercase Letter 882
 
12.6%
Space Separator 664
 
9.5%
Other Punctuation 44
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 879
16.3%
u 498
 
9.2%
n 405
 
7.5%
o 375
 
7.0%
t 359
 
6.7%
i 352
 
6.5%
s 345
 
6.4%
l 308
 
5.7%
d 299
 
5.5%
m 285
 
5.3%
Other values (13) 1288
23.9%
Uppercase Letter
ValueCountFrequency (%)
C 249
28.2%
E 238
27.0%
J 41
 
4.6%
S 40
 
4.5%
H 38
 
4.3%
W 37
 
4.2%
M 32
 
3.6%
L 25
 
2.8%
T 25
 
2.8%
B 24
 
2.7%
Other values (11) 133
15.1%
Other Punctuation
ValueCountFrequency (%)
. 35
79.5%
, 6
 
13.6%
' 3
 
6.8%
Space Separator
ValueCountFrequency (%)
660
99.4%
  4
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 6275
89.9%
Common 708
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 879
14.0%
u 498
 
7.9%
n 405
 
6.5%
o 375
 
6.0%
t 359
 
5.7%
i 352
 
5.6%
s 345
 
5.5%
l 308
 
4.9%
d 299
 
4.8%
m 285
 
4.5%
Other values (34) 2170
34.6%
Common
ValueCountFrequency (%)
660
93.2%
. 35
 
4.9%
, 6
 
0.8%
  4
 
0.6%
' 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6979
99.9%
None 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 879
 
12.6%
660
 
9.5%
u 498
 
7.1%
n 405
 
5.8%
o 375
 
5.4%
t 359
 
5.1%
i 352
 
5.0%
s 345
 
4.9%
l 308
 
4.4%
d 299
 
4.3%
Other values (38) 2499
35.8%
None
ValueCountFrequency (%)
  4
100.0%

school_type
Text

MISSING 

Distinct13
Distinct (%)12.5%
Missing331
Missing (%)76.1%
Memory size17.8 KiB
2023-12-09T22:17:23.365355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length27
Mean length15.375
Min length10

Characters and Unicode

Total characters1599
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st rowSpecialized School
2nd rowNYC P-Tech 9-14 School
3rd rowInternational School
4th rowAll-Boys School
5th rowCTE School
ValueCountFrequency (%)
school 104
44.8%
cte 40
 
17.2%
consortium 20
 
8.6%
international 16
 
6.9%
new 12
 
5.2%
specialized 9
 
3.9%
all-girls 8
 
3.4%
nyc 6
 
2.6%
p-tech 6
 
2.6%
9-14 6
 
2.6%
Other values (2) 5
 
2.2%
2023-12-09T22:17:23.661707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 267
16.7%
l 159
 
9.9%
128
 
8.0%
c 119
 
7.4%
S 113
 
7.1%
h 110
 
6.9%
n 68
 
4.3%
C 66
 
4.1%
i 62
 
3.9%
t 52
 
3.3%
Other values (25) 455
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1087
68.0%
Uppercase Letter 333
 
20.8%
Space Separator 128
 
8.0%
Dash Punctuation 25
 
1.6%
Decimal Number 18
 
1.1%
Other Punctuation 8
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 267
24.6%
l 159
14.6%
c 119
10.9%
h 110
10.1%
n 68
 
6.3%
i 62
 
5.7%
t 52
 
4.8%
e 52
 
4.8%
r 44
 
4.0%
a 41
 
3.8%
Other values (8) 113
10.4%
Uppercase Letter
ValueCountFrequency (%)
S 113
33.9%
C 66
19.8%
T 46
13.8%
E 40
 
12.0%
N 18
 
5.4%
I 16
 
4.8%
A 11
 
3.3%
G 8
 
2.4%
Y 6
 
1.8%
P 6
 
1.8%
Decimal Number
ValueCountFrequency (%)
9 6
33.3%
1 6
33.3%
4 6
33.3%
Space Separator
ValueCountFrequency (%)
128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1420
88.8%
Common 179
 
11.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 267
18.8%
l 159
11.2%
c 119
 
8.4%
S 113
 
8.0%
h 110
 
7.7%
n 68
 
4.8%
C 66
 
4.6%
i 62
 
4.4%
t 52
 
3.7%
e 52
 
3.7%
Other values (19) 352
24.8%
Common
ValueCountFrequency (%)
128
71.5%
- 25
 
14.0%
, 8
 
4.5%
9 6
 
3.4%
1 6
 
3.4%
4 6
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 267
16.7%
l 159
 
9.9%
128
 
8.0%
c 119
 
7.4%
S 113
 
7.1%
h 110
 
6.9%
n 68
 
4.3%
C 66
 
4.1%
i 62
 
3.9%
t 52
 
3.3%
Other values (25) 455
28.5%

overview_paragraph
Text

Distinct434
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size377.2 KiB
2023-12-09T22:17:24.039772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1531
Median length717.5
Mean length622.2880184
Min length32

Characters and Unicode

Total characters270073
Distinct characters87
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique434 ?
Unique (%)100.0%

Sample

1st rowFrederick Douglass Academy (FDA) VI High School is a high school built on Dr. Lorraine Monroe’s vision of academic and personal excellence for all students. The emphasis on college preparation is supported by a challenging academic program and cultural enrichment. A set of core rules visible at every Frederick Douglass Academy signals the seriousness of purpose for the school, its students and teachers. All students must adhere to a code of student conduct, the Scholar’s Creed and a strict uniform code. Students are also required to participate in extensive after-school academic enrichment programs.
2nd rowAt Life Academy High School for Film and Music, we infuse the study of film, the art of filmmaking, audio production and new media into engaging, student-centered and project-based courses. We focus on building communication skills in writing, presentation and creativity. Our Advisory program helps each student develop personal relationships and positive citizenship. We seek students who want to learn in an exciting atmosphere of excellence and creative collaboration.
3rd rowThe Frederick Douglass Academy IV (FDA IV) Secondary School is a place of scholarship. Our students are considered scholars. We create an atmosphere of order, civility, maturity and seriousness of purpose. A set of core rules referred to as the ‘twelve non-negotiables’ establish and maintain this environment. Scholars at the Frederick Douglas Academy IV Secondary School are instilled with a Scholar’s Creed, adapted from the Morehouse College Students’ Creed, that reinforces the school’s cohesive culture, underscores its high expectations and builds the scholars’ sense of pride in their school and themselves.
4th rowOur mission is to engage, inspire, and educate our students so that they develop skills to succeed in college and beyond. Our students work in small groups, guided by skilled and caring teachers, to solve challenging problems. Each student is well-known by staff members, and is assigned an advisor who works closely with them each week to monitor their progress. We celebrate successes and students are recognized for their accomplishments.
5th rowWe enjoy an international reputation as the first and foremost high school dedicated to nurturing students gifted in the arts. Our mission is to provide an opportunity for students to pursue both a rigorous conservatory-style training and a challenging academic program. Our building features world-class facilities including a concert hall; art, dance, music, recording and theater studios, science and computer labs, and an art gallery. Almost all of our graduates continue their studies, gaining admission to highly selective schools. Our graduates have distinguished themselves in virtually every field, including the arts and sciences, medicine, law, business, education and public service.
ValueCountFrequency (%)
and 2308
 
5.8%
the 1430
 
3.6%
to 1365
 
3.4%
students 1095
 
2.7%
of 1068
 
2.7%
a 975
 
2.4%
in 963
 
2.4%
our 864
 
2.2%
school 675
 
1.7%
for 536
 
1.3%
Other values (3732) 28664
71.8%
2023-12-09T22:17:24.620380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39574
14.7%
e 26160
 
9.7%
t 18056
 
6.7%
a 17123
 
6.3%
n 16860
 
6.2%
i 16381
 
6.1%
o 16340
 
6.1%
r 15225
 
5.6%
s 15145
 
5.6%
l 10761
 
4.0%
Other values (77) 78448
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 218271
80.8%
Space Separator 39575
 
14.7%
Uppercase Letter 6394
 
2.4%
Other Punctuation 4162
 
1.5%
Dash Punctuation 758
 
0.3%
Decimal Number 361
 
0.1%
Close Punctuation 181
 
0.1%
Open Punctuation 181
 
0.1%
Final Punctuation 156
 
0.1%
Initial Punctuation 32
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26160
12.0%
t 18056
 
8.3%
a 17123
 
7.8%
n 16860
 
7.7%
i 16381
 
7.5%
o 16340
 
7.5%
r 15225
 
7.0%
s 15145
 
6.9%
l 10761
 
4.9%
c 9995
 
4.6%
Other values (18) 56225
25.8%
Uppercase Letter
ValueCountFrequency (%)
S 860
13.5%
A 659
 
10.3%
C 610
 
9.5%
T 516
 
8.1%
W 437
 
6.8%
O 416
 
6.5%
E 388
 
6.1%
H 313
 
4.9%
L 250
 
3.9%
B 239
 
3.7%
Other values (16) 1706
26.7%
Other Punctuation
ValueCountFrequency (%)
, 2021
48.6%
. 1915
46.0%
' 68
 
1.6%
/ 51
 
1.2%
: 45
 
1.1%
& 24
 
0.6%
; 16
 
0.4%
! 10
 
0.2%
% 6
 
0.1%
? 6
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 105
29.1%
0 74
20.5%
2 72
19.9%
6 31
 
8.6%
9 28
 
7.8%
5 21
 
5.8%
4 15
 
4.2%
3 10
 
2.8%
8 4
 
1.1%
7 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 708
93.4%
– 36
 
4.7%
— 14
 
1.8%
Space Separator
ValueCountFrequency (%)
39574
> 99.9%
  1
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
’ 144
92.3%
” 12
 
7.7%
Initial Punctuation
ValueCountFrequency (%)
‘ 20
62.5%
“ 12
37.5%
Close Punctuation
ValueCountFrequency (%)
) 181
100.0%
Open Punctuation
ValueCountFrequency (%)
( 181
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 224665
83.2%
Common 45408
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26160
11.6%
t 18056
 
8.0%
a 17123
 
7.6%
n 16860
 
7.5%
i 16381
 
7.3%
o 16340
 
7.3%
r 15225
 
6.8%
s 15145
 
6.7%
l 10761
 
4.8%
c 9995
 
4.4%
Other values (44) 62619
27.9%
Common
ValueCountFrequency (%)
39574
87.2%
, 2021
 
4.5%
. 1915
 
4.2%
- 708
 
1.6%
) 181
 
0.4%
( 181
 
0.4%
’ 144
 
0.3%
1 105
 
0.2%
0 74
 
0.2%
2 72
 
0.2%
Other values (23) 433
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 269831
99.9%
Punctuation 238
 
0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39574
14.7%
e 26160
 
9.7%
t 18056
 
6.7%
a 17123
 
6.3%
n 16860
 
6.2%
i 16381
 
6.1%
o 16340
 
6.1%
r 15225
 
5.6%
s 15145
 
5.6%
l 10761
 
4.0%
Other values (68) 78206
29.0%
Punctuation
ValueCountFrequency (%)
’ 144
60.5%
– 36
 
15.1%
‘ 20
 
8.4%
— 14
 
5.9%
“ 12
 
5.0%
” 12
 
5.0%
None
ValueCountFrequency (%)
é 2
50.0%
  1
25.0%
ó 1
25.0%

program_highlights
Text

Distinct434
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size187.6 KiB
2023-12-09T22:17:24.984338image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1138
Median length445.5
Mean length369.6359447
Min length13

Characters and Unicode

Total characters160422
Distinct characters79
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique434 ?
Unique (%)100.0%

Sample

1st rowAdvisory, Graphic Arts Design, Teaching Internship; College tours: citywide for freshmen, statewide for sophomores and out-of-state for juniors; National and international educational trips
2nd rowCollege Now, iLEARN courses, Art and Film Production courses including film, set design, audio production, cinematography, animation, storyboarding art
3rd rowCollege Now with Medgar Evers College, Fresh Prep Core, Science, Technology, Engineering & Mathematics (STEM) Robotics with New York City College of Technology, Dance4Peace
4th rowAdvanced Placement courses, Electives courses including: Art & Design, Criminal Justice, Entrepreneurship, Careers & Internships, and Advanced Art; Student Learning Communities, Internship Opportunities, Individualized Student Programming, Credit-bearing Online Courses (iLearn) and After-school Enrichment Classes; College Now & JumpStart (Credit-bearing College Courses)
5th rowStudents have a daily program that includes both a multi-period conservatory studio block and a full college preparatory academic course load. The studio majors are: Dance, Drama, Fine Arts, Instrumental Music, Technical Theater and Vocal Music. Each studio has a four-year sequence of courses and opportunities for students to participate in performances and exhibitions. Students completing the applicable NYC Studio Comprehensive exam receive a special endorsement on their diploma. Honors courses are offered in all academic areas starting in the freshman year, leading to a full complement of Advanced Placement courses.
ValueCountFrequency (%)
and 924
 
4.4%
college 731
 
3.5%
in 401
 
1.9%
program 355
 
1.7%
the 318
 
1.5%
of 299
 
1.4%
students 246
 
1.2%
to 243
 
1.2%
courses 234
 
1.1%
now 220
 
1.0%
Other values (2822) 16983
81.0%
2023-12-09T22:17:25.529103image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20553
 
12.8%
e 14552
 
9.1%
r 9768
 
6.1%
i 9736
 
6.1%
n 9726
 
6.1%
o 9518
 
5.9%
a 9217
 
5.7%
t 8679
 
5.4%
s 8187
 
5.1%
l 5990
 
3.7%
Other values (69) 54496
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 119282
74.4%
Space Separator 20553
 
12.8%
Uppercase Letter 13549
 
8.4%
Other Punctuation 5294
 
3.3%
Dash Punctuation 525
 
0.3%
Decimal Number 474
 
0.3%
Close Punctuation 356
 
0.2%
Open Punctuation 355
 
0.2%
Final Punctuation 16
 
< 0.1%
Math Symbol 15
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14552
12.2%
r 9768
 
8.2%
i 9736
 
8.2%
n 9726
 
8.2%
o 9518
 
8.0%
a 9217
 
7.7%
t 8679
 
7.3%
s 8187
 
6.9%
l 5990
 
5.0%
c 5347
 
4.5%
Other values (16) 28562
23.9%
Uppercase Letter
ValueCountFrequency (%)
C 1912
14.1%
S 1515
11.2%
A 1497
11.0%
P 1215
 
9.0%
T 872
 
6.4%
E 757
 
5.6%
M 635
 
4.7%
I 595
 
4.4%
N 506
 
3.7%
L 488
 
3.6%
Other values (16) 3557
26.3%
Decimal Number
ValueCountFrequency (%)
1 187
39.5%
2 72
 
15.2%
0 71
 
15.0%
9 62
 
13.1%
3 23
 
4.9%
4 20
 
4.2%
5 16
 
3.4%
6 12
 
2.5%
7 6
 
1.3%
8 5
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 3831
72.4%
; 758
 
14.3%
. 186
 
3.5%
: 167
 
3.2%
& 155
 
2.9%
/ 125
 
2.4%
' 66
 
1.2%
@ 4
 
0.1%
! 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 524
99.8%
– 1
 
0.2%
Space Separator
ValueCountFrequency (%)
20553
100.0%
Close Punctuation
ValueCountFrequency (%)
) 356
100.0%
Open Punctuation
ValueCountFrequency (%)
( 355
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 15
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 132831
82.8%
Common 27591
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14552
 
11.0%
r 9768
 
7.4%
i 9736
 
7.3%
n 9726
 
7.3%
o 9518
 
7.2%
a 9217
 
6.9%
t 8679
 
6.5%
s 8187
 
6.2%
l 5990
 
4.5%
c 5347
 
4.0%
Other values (42) 42111
31.7%
Common
ValueCountFrequency (%)
20553
74.5%
, 3831
 
13.9%
; 758
 
2.7%
- 524
 
1.9%
) 356
 
1.3%
( 355
 
1.3%
1 187
 
0.7%
. 186
 
0.7%
: 167
 
0.6%
& 155
 
0.6%
Other values (17) 519
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160402
> 99.9%
Punctuation 20
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20553
 
12.8%
e 14552
 
9.1%
r 9768
 
6.1%
i 9736
 
6.1%
n 9726
 
6.1%
o 9518
 
5.9%
a 9217
 
5.7%
t 8679
 
5.4%
s 8187
 
5.1%
l 5990
 
3.7%
Other values (66) 54476
34.0%
Punctuation
ValueCountFrequency (%)
’ 16
80.0%
‘ 3
 
15.0%
– 1
 
5.0%

language_classes
Text

MISSING 

Distinct74
Distinct (%)18.0%
Missing23
Missing (%)5.3%
Memory size30.2 KiB
2023-12-09T22:17:25.748192image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length141
Median length7
Mean length15.99514563
Min length5

Characters and Unicode

Total characters6590
Distinct characters48
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)13.1%

Sample

1st rowSpanish
2nd rowSpanish
3rd rowFrench, Spanish
4th rowSpanish
5th rowFrench, Italian, Japanese, Spanish
ValueCountFrequency (%)
spanish 393
45.4%
french 106
 
12.3%
chinese 50
 
5.8%
language 43
 
5.0%
italian 41
 
4.7%
native 30
 
3.5%
arts 30
 
3.5%
mandarin 26
 
3.0%
latin 25
 
2.9%
japanese 15
 
1.7%
Other values (23) 106
 
12.3%
2023-12-09T22:17:26.146322image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 795
12.1%
a 758
11.5%
i 627
9.5%
h 554
8.4%
s 526
 
8.0%
459
 
7.0%
p 412
 
6.3%
S 406
 
6.2%
e 387
 
5.9%
, 283
 
4.3%
Other values (38) 1383
21.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4911
74.5%
Uppercase Letter 861
 
13.1%
Space Separator 459
 
7.0%
Other Punctuation 293
 
4.4%
Close Punctuation 32
 
0.5%
Open Punctuation 32
 
0.5%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 795
16.2%
a 758
15.4%
i 627
12.8%
h 554
11.3%
s 526
10.7%
p 412
8.4%
e 387
7.9%
r 216
 
4.4%
t 146
 
3.0%
c 136
 
2.8%
Other values (11) 354
7.2%
Uppercase Letter
ValueCountFrequency (%)
S 406
47.2%
F 106
 
12.3%
L 68
 
7.9%
A 57
 
6.6%
C 57
 
6.6%
I 41
 
4.8%
N 34
 
3.9%
M 30
 
3.5%
J 15
 
1.7%
G 12
 
1.4%
Other values (7) 35
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 283
96.6%
/ 4
 
1.4%
: 4
 
1.4%
. 2
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 31
96.9%
] 1
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 31
96.9%
[ 1
 
3.1%
Space Separator
ValueCountFrequency (%)
459
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5772
87.6%
Common 818
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 795
13.8%
a 758
13.1%
i 627
10.9%
h 554
9.6%
s 526
9.1%
p 412
7.1%
S 406
7.0%
e 387
6.7%
r 216
 
3.7%
t 146
 
2.5%
Other values (28) 945
16.4%
Common
ValueCountFrequency (%)
459
56.1%
, 283
34.6%
) 31
 
3.8%
( 31
 
3.8%
/ 4
 
0.5%
: 4
 
0.5%
- 2
 
0.2%
. 2
 
0.2%
[ 1
 
0.1%
] 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 795
12.1%
a 758
11.5%
i 627
9.5%
h 554
8.4%
s 526
 
8.0%
459
 
7.0%
p 412
 
6.3%
S 406
 
6.2%
e 387
 
5.9%
, 283
 
4.3%
Other values (38) 1383
21.0%

advancedplacement_courses
Text

MISSING 

Distinct290
Distinct (%)85.3%
Missing95
Missing (%)21.8%
Memory size66.1 KiB
2023-12-09T22:17:26.413910image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length687
Median length223
Mean length132.7088235
Min length7

Characters and Unicode

Total characters45121
Distinct characters49
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique268 ?
Unique (%)78.8%

Sample

1st rowCalculus AB, English Language and Composition, English Literature and Composition, United States History
2nd rowEnglish Language and Composition, United States History
3rd rowArt History, English Language and Composition, English Literature and Composition, United States Government and Politics
4th rowArt History, Biology, Calculus AB, Calculus BC, Chemistry, Comparative Government and Politics, English Language and Composition, English Literature and Composition, Environmental Science, European History, French Language and Culture, Italian Language and Culture, Japanese Language and Culture, Music Theory, Physics B, Psychology, Spanish Language and Culture, Statistics, Studio Art: 2-D Design, Studio Art: 3-D Design, Studio Art: Drawing, United States Government and Politics, United States History, World History
5th rowEnglish Literature and Composition, Microeconomics, Spanish Language and Culture, United States History
ValueCountFrequency (%)
and 759
 
13.5%
english 393
 
7.0%
composition 393
 
7.0%
history 378
 
6.7%
language 360
 
6.4%
united 291
 
5.2%
states 291
 
5.2%
literature 286
 
5.1%
culture 253
 
4.5%
calculus 233
 
4.1%
Other values (51) 1979
35.2%
2023-12-09T22:17:26.866722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5291
 
11.7%
i 3436
 
7.6%
t 3249
 
7.2%
n 3153
 
7.0%
a 2843
 
6.3%
o 2678
 
5.9%
e 2651
 
5.9%
s 2559
 
5.7%
r 1878
 
4.2%
u 1769
 
3.9%
Other values (39) 15614
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32894
72.9%
Space Separator 5291
 
11.7%
Uppercase Letter 5092
 
11.3%
Other Punctuation 1788
 
4.0%
Dash Punctuation 24
 
0.1%
Decimal Number 24
 
0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3436
10.4%
t 3249
9.9%
n 3153
9.6%
a 2843
8.6%
o 2678
 
8.1%
e 2651
 
8.1%
s 2559
 
7.8%
r 1878
 
5.7%
u 1769
 
5.4%
l 1617
 
4.9%
Other values (10) 7061
21.5%
Uppercase Letter
ValueCountFrequency (%)
C 1109
21.8%
S 697
13.7%
L 648
12.7%
E 516
10.1%
B 447
8.8%
H 402
 
7.9%
A 295
 
5.8%
U 291
 
5.7%
P 232
 
4.6%
G 125
 
2.5%
Other values (9) 330
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 1699
95.0%
: 83
 
4.6%
/ 4
 
0.2%
. 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 14
58.3%
3 10
41.7%
Space Separator
ValueCountFrequency (%)
5291
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37986
84.2%
Common 7135
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3436
 
9.0%
t 3249
 
8.6%
n 3153
 
8.3%
a 2843
 
7.5%
o 2678
 
7.0%
e 2651
 
7.0%
s 2559
 
6.7%
r 1878
 
4.9%
u 1769
 
4.7%
l 1617
 
4.3%
Other values (29) 12153
32.0%
Common
ValueCountFrequency (%)
5291
74.2%
, 1699
 
23.8%
: 83
 
1.2%
- 24
 
0.3%
2 14
 
0.2%
3 10
 
0.1%
/ 4
 
0.1%
( 4
 
0.1%
) 4
 
0.1%
. 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5291
 
11.7%
i 3436
 
7.6%
t 3249
 
7.2%
n 3153
 
7.0%
a 2843
 
6.3%
o 2678
 
5.9%
e 2651
 
5.9%
s 2559
 
5.7%
r 1878
 
4.2%
u 1769
 
3.9%
Other values (39) 15614
34.6%

online_ap_courses
Text

MISSING 

Distinct57
Distinct (%)89.1%
Missing371
Missing (%)85.3%
Memory size19.9 KiB
2023-12-09T22:17:27.126735image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length378
Median length80.5
Mean length73.71875
Min length7

Characters and Unicode

Total characters4718
Distinct characters47
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)81.2%

Sample

1st rowBiology, Physics B
2nd rowBiology, English Literature and Composition, European History, United States History, World History
3rd rowFrench Language and Culture
4th rowArt History, Calculus BC, English Language and Composition, English Literature and Composition, United States History, World History
5th rowEnglish Literature and Composition, Macroeconomics, World History
ValueCountFrequency (%)
and 67
 
11.4%
history 47
 
8.0%
language 40
 
6.8%
english 29
 
4.9%
composition 29
 
4.9%
states 28
 
4.7%
united 28
 
4.7%
biology 27
 
4.6%
culture 26
 
4.4%
literature 17
 
2.9%
Other values (48) 252
42.7%
2023-12-09T22:17:27.573100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
533
 
11.3%
i 341
 
7.2%
t 324
 
6.9%
o 323
 
6.8%
n 317
 
6.7%
e 293
 
6.2%
a 268
 
5.7%
s 262
 
5.6%
r 215
 
4.6%
, 172
 
3.6%
Other values (37) 1670
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3468
73.5%
Space Separator 533
 
11.3%
Uppercase Letter 526
 
11.1%
Other Punctuation 183
 
3.9%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 341
9.8%
t 324
9.3%
o 323
9.3%
n 317
 
9.1%
e 293
 
8.4%
a 268
 
7.7%
s 262
 
7.6%
r 215
 
6.2%
l 163
 
4.7%
u 160
 
4.6%
Other values (11) 802
23.1%
Uppercase Letter
ValueCountFrequency (%)
C 99
18.8%
S 66
12.5%
L 57
10.8%
B 55
10.5%
H 50
9.5%
E 44
8.4%
A 33
 
6.3%
P 30
 
5.7%
U 28
 
5.3%
M 16
 
3.0%
Other values (6) 48
9.1%
Other Punctuation
ValueCountFrequency (%)
, 172
94.0%
: 7
 
3.8%
/ 2
 
1.1%
. 2
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
533
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3994
84.7%
Common 724
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 341
 
8.5%
t 324
 
8.1%
o 323
 
8.1%
n 317
 
7.9%
e 293
 
7.3%
a 268
 
6.7%
s 262
 
6.6%
r 215
 
5.4%
l 163
 
4.1%
u 160
 
4.0%
Other values (27) 1328
33.2%
Common
ValueCountFrequency (%)
533
73.6%
, 172
 
23.8%
: 7
 
1.0%
( 2
 
0.3%
/ 2
 
0.3%
) 2
 
0.3%
. 2
 
0.3%
- 2
 
0.3%
2 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4718
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
533
 
11.3%
i 341
 
7.2%
t 324
 
6.9%
o 323
 
6.8%
n 317
 
6.7%
e 293
 
6.2%
a 268
 
5.7%
s 262
 
5.6%
r 215
 
4.6%
, 172
 
3.6%
Other values (37) 1670
35.4%

online_language_courses
Text

MISSING 

Distinct40
Distinct (%)54.8%
Missing362
Missing (%)83.2%
Memory size17.4 KiB
2023-12-09T22:17:27.813059image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length169
Median length90
Mean length27.06849315
Min length6

Characters and Unicode

Total characters1976
Distinct characters47
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)45.2%

Sample

1st rowFrench, Spanish
2nd rowSpanish
3rd rowSpanish
4th rowAmerican Sign Language, Arabic, Chinese (Mandarin), English, French, German, Hebrew, Italian, Japanese, Korean, Latin, Modern Greek, Polish, Portuguese, Russian, Spanish
5th rowFrench, Spanish
ValueCountFrequency (%)
spanish 56
22.7%
french 36
14.6%
chinese 21
 
8.5%
german 10
 
4.0%
latin 9
 
3.6%
italian 9
 
3.6%
japanese 9
 
3.6%
mandarin 9
 
3.6%
english 8
 
3.2%
language 6
 
2.4%
Other values (32) 74
30.0%
2023-12-09T22:17:28.224026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 212
 
10.7%
180
 
9.1%
a 180
 
9.1%
e 173
 
8.8%
i 145
 
7.3%
s 128
 
6.5%
h 127
 
6.4%
, 122
 
6.2%
r 91
 
4.6%
p 69
 
3.5%
Other values (37) 549
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1397
70.7%
Uppercase Letter 237
 
12.0%
Space Separator 180
 
9.1%
Other Punctuation 131
 
6.6%
Close Punctuation 14
 
0.7%
Open Punctuation 14
 
0.7%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 212
15.2%
a 180
12.9%
e 173
12.4%
i 145
10.4%
s 128
9.2%
h 127
9.1%
r 91
6.5%
p 69
 
4.9%
t 54
 
3.9%
c 52
 
3.7%
Other values (12) 166
11.9%
Uppercase Letter
ValueCountFrequency (%)
S 57
24.1%
F 36
15.2%
C 27
11.4%
L 15
 
6.3%
A 15
 
6.3%
E 12
 
5.1%
G 12
 
5.1%
M 10
 
4.2%
J 9
 
3.8%
I 9
 
3.8%
Other values (7) 35
14.8%
Other Punctuation
ValueCountFrequency (%)
, 122
93.1%
/ 3
 
2.3%
. 3
 
2.3%
: 3
 
2.3%
Space Separator
ValueCountFrequency (%)
180
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1634
82.7%
Common 342
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 212
13.0%
a 180
11.0%
e 173
10.6%
i 145
 
8.9%
s 128
 
7.8%
h 127
 
7.8%
r 91
 
5.6%
p 69
 
4.2%
S 57
 
3.5%
t 54
 
3.3%
Other values (29) 398
24.4%
Common
ValueCountFrequency (%)
180
52.6%
, 122
35.7%
) 14
 
4.1%
( 14
 
4.1%
/ 3
 
0.9%
- 3
 
0.9%
. 3
 
0.9%
: 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1976
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 212
 
10.7%
180
 
9.1%
a 180
 
9.1%
e 173
 
8.8%
i 145
 
7.3%
s 128
 
6.5%
h 127
 
6.4%
, 122
 
6.2%
r 91
 
4.6%
p 69
 
3.5%
Other values (37) 549
27.8%

extracurricular_activities
Text

UNIQUE 

Distinct435
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size169.1 KiB
2023-12-09T22:17:28.636897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1178
Median length417
Mean length329.7977011
Min length23

Characters and Unicode

Total characters143462
Distinct characters83
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)100.0%

Sample

1st rowAfter-school Program, Book, Writing, Homework Help, Honor Society, Journalism, Lunch & Learn, PSAT and SAT Prep, Saturday Program, Step Team, Student Government, Summer Institute, Video, Tech, Yearbook, Computer Graphics, Robotics, Cheerleading
2nd rowFilm, Music, Talent Show, Holiday Concert, Student Council, After school tutoring in content areas, iLEARN courses, and other programs of student interest based on grant funding.
3rd rowAfter-school and Saturday Programs, Art Studio Group, Book, Cheerleading Team, Chess Team, Dance, Dance Ensemble, Homework Help, Lunch and Learn, Peer Mediation, Music, PSAT/SAT Prep, Scholars Government Association (SGA), Step Team, Summer Institute, Achieving Change in our Neighborhood (Teen Action), Violin, String Instruments, CHAMPS, School Leadership Team, Financial Literacy, Yoga, Anti-Bullying, Violence Prevention, Yearbook
4th rowYouth Court, Student Government, Youth Service, Youth Service Leaders, Art, Graffiti Mural, Yearbook, Homework Help & Tutoring Services, Regents Prep, Saturday Academy, Senior Committee, Video Game, Yoga, Dance, Digital Media, Book, Chess, Soccer, Softball, Basketball Intramurals, National Honor Society
5th rowAmnesty International, Anime, Annual Musical, Arista, Art Exhibits, ASPIRA, Black Student Union, Chinese Student Association, Claymazing, Comic Book, Cult Classics, Dance Programs, DaVinci Scholars Program, Debate Team, Disney VoluntEars, Drama Festivals, Environmental, Fashion, Film, Future Voters of America, Gay/Straight Alliance, Girls Learn International, Habitat for Humanity, Harry Potter, Independent Film, Jewish Union, Literary Magazine, Math Team, Mock Trial, Moot Court, Murals, National Honor Society, National Language Honors Society, Newspaper, Orchestral and Vocal Concerts, Random Acts of Kindness, Red Cross, Relay For Life, School Leadership Team (SLT), Science Outreach League, Shamisen, Social Action, Splashes of Hope, Student Government Organization, Ukulele For Good, Yearbook
ValueCountFrequency (%)
student 488
 
2.7%
and 428
 
2.4%
team 314
 
1.7%
dance 285
 
1.6%
society 258
 
1.4%
government 252
 
1.4%
peer 222
 
1.2%
tutoring 221
 
1.2%
honor 218
 
1.2%
school 216
 
1.2%
Other values (2616) 15172
83.9%
2023-12-09T22:17:29.237703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17662
 
12.3%
e 11936
 
8.3%
o 8677
 
6.0%
a 8607
 
6.0%
r 8312
 
5.8%
n 8241
 
5.7%
t 8230
 
5.7%
i 7926
 
5.5%
, 7539
 
5.3%
s 5219
 
3.6%
Other values (73) 51113
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 98382
68.6%
Uppercase Letter 18204
 
12.7%
Space Separator 17662
 
12.3%
Other Punctuation 8175
 
5.7%
Dash Punctuation 351
 
0.2%
Open Punctuation 284
 
0.2%
Close Punctuation 284
 
0.2%
Decimal Number 106
 
0.1%
Final Punctuation 10
 
< 0.1%
Initial Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11936
12.1%
o 8677
 
8.8%
a 8607
 
8.7%
r 8312
 
8.4%
n 8241
 
8.4%
t 8230
 
8.4%
i 7926
 
8.1%
s 5219
 
5.3%
l 4401
 
4.5%
c 3825
 
3.9%
Other values (17) 23008
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 2674
14.7%
C 2090
11.5%
A 1608
 
8.8%
T 1345
 
7.4%
P 1339
 
7.4%
M 1184
 
6.5%
D 970
 
5.3%
G 765
 
4.2%
H 643
 
3.5%
N 640
 
3.5%
Other values (16) 4946
27.2%
Other Punctuation
ValueCountFrequency (%)
, 7539
92.2%
/ 180
 
2.2%
' 148
 
1.8%
; 130
 
1.6%
& 68
 
0.8%
. 58
 
0.7%
: 45
 
0.6%
! 5
 
0.1%
? 1
 
< 0.1%
¡ 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 27
25.5%
2 23
21.7%
1 16
15.1%
3 12
11.3%
4 8
 
7.5%
5 7
 
6.6%
9 7
 
6.6%
8 4
 
3.8%
6 2
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 350
99.7%
– 1
 
0.3%
Final Punctuation
ValueCountFrequency (%)
’ 9
90.0%
” 1
 
10.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
50.0%
‘ 1
50.0%
Math Symbol
ValueCountFrequency (%)
= 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
17662
100.0%
Open Punctuation
ValueCountFrequency (%)
( 284
100.0%
Close Punctuation
ValueCountFrequency (%)
) 284
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 116586
81.3%
Common 26876
 
18.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11936
 
10.2%
o 8677
 
7.4%
a 8607
 
7.4%
r 8312
 
7.1%
n 8241
 
7.1%
t 8230
 
7.1%
i 7926
 
6.8%
s 5219
 
4.5%
l 4401
 
3.8%
c 3825
 
3.3%
Other values (43) 41212
35.3%
Common
ValueCountFrequency (%)
17662
65.7%
, 7539
28.1%
- 350
 
1.3%
( 284
 
1.1%
) 284
 
1.1%
/ 180
 
0.7%
' 148
 
0.6%
; 130
 
0.5%
& 68
 
0.3%
. 58
 
0.2%
Other values (20) 173
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143447
> 99.9%
Punctuation 13
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17662
 
12.3%
e 11936
 
8.3%
o 8677
 
6.0%
a 8607
 
6.0%
r 8312
 
5.8%
n 8241
 
5.7%
t 8230
 
5.7%
i 7926
 
5.5%
, 7539
 
5.3%
s 5219
 
3.6%
Other values (66) 51098
35.6%
Punctuation
ValueCountFrequency (%)
’ 9
69.2%
” 1
 
7.7%
– 1
 
7.7%
“ 1
 
7.7%
‘ 1
 
7.7%
None
ValueCountFrequency (%)
ñ 1
50.0%
¡ 1
50.0%

psal_sports_boys
Text

MISSING 

Distinct262
Distinct (%)70.2%
Missing62
Missing (%)14.3%
Memory size48.4 KiB
2023-12-09T22:17:29.472660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length225
Median length138
Mean length70.24396783
Min length6

Characters and Unicode

Total characters26201
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique215 ?
Unique (%)57.6%

Sample

1st rowBasketball, Cross Country, Indoor Track, Outdoor Track, Soccer, Softball, Swimming, Tennis, Volleyball
2nd rowBasketball, Bowling, Indoor Track, Soccer, Softball, Volleyball
3rd rowBasketball, Outdoor Track, Softball, Tennis, Volleyball
4th rowBasketball, Bowling, Cross Country, Fencing, Gymnastics, Handball, Indoor Track, Outdoor Track, Soccer, Softball, Swimming, Volleyball
5th rowBasketball, Bowling, Tennis, Volleyball
ValueCountFrequency (%)
basketball 409
12.9%
volleyball 349
11.0%
track 340
10.7%
softball 312
9.8%
outdoor 182
 
5.7%
jv 180
 
5.7%
soccer 173
 
5.4%
171
 
5.4%
indoor 158
 
5.0%
tennis 148
 
4.7%
Other values (20) 754
23.7%
2023-12-09T22:17:29.876550image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 3226
 
12.3%
2820
 
10.8%
a 2056
 
7.8%
o 2040
 
7.8%
, 1781
 
6.8%
r 1208
 
4.6%
b 1190
 
4.5%
e 1186
 
4.5%
t 1141
 
4.4%
s 1006
 
3.8%
Other values (29) 8547
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18248
69.6%
Uppercase Letter 3179
 
12.1%
Space Separator 2820
 
10.8%
Other Punctuation 1954
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 3226
17.7%
a 2056
11.3%
o 2040
11.2%
r 1208
 
6.6%
b 1190
 
6.5%
e 1186
 
6.5%
t 1141
 
6.3%
s 1006
 
5.5%
n 957
 
5.2%
c 778
 
4.3%
Other values (10) 3460
19.0%
Uppercase Letter
ValueCountFrequency (%)
B 548
17.2%
S 541
17.0%
V 529
16.6%
T 488
15.4%
C 297
9.3%
O 182
 
5.7%
J 180
 
5.7%
I 158
 
5.0%
H 71
 
2.2%
G 60
 
1.9%
Other values (5) 125
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 1781
91.1%
& 171
 
8.8%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
2820
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21427
81.8%
Common 4774
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 3226
15.1%
a 2056
 
9.6%
o 2040
 
9.5%
r 1208
 
5.6%
b 1190
 
5.6%
e 1186
 
5.5%
t 1141
 
5.3%
s 1006
 
4.7%
n 957
 
4.5%
c 778
 
3.6%
Other values (25) 6639
31.0%
Common
ValueCountFrequency (%)
2820
59.1%
, 1781
37.3%
& 171
 
3.6%
. 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26201
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 3226
 
12.3%
2820
 
10.8%
a 2056
 
7.8%
o 2040
 
7.8%
, 1781
 
6.8%
r 1208
 
4.6%
b 1190
 
4.5%
e 1186
 
4.5%
t 1141
 
4.4%
s 1006
 
3.8%
Other values (29) 8547
32.6%

psal_sports_girls
Text

MISSING 

Distinct262
Distinct (%)70.2%
Missing62
Missing (%)14.3%
Memory size48.4 KiB
2023-12-09T22:17:30.112961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length225
Median length138
Mean length70.24396783
Min length6

Characters and Unicode

Total characters26201
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique215 ?
Unique (%)57.6%

Sample

1st rowBasketball, Cross Country, Indoor Track, Outdoor Track, Soccer, Softball, Swimming, Tennis, Volleyball
2nd rowBasketball, Bowling, Indoor Track, Soccer, Softball, Volleyball
3rd rowBasketball, Outdoor Track, Softball, Tennis, Volleyball
4th rowBasketball, Bowling, Cross Country, Fencing, Gymnastics, Handball, Indoor Track, Outdoor Track, Soccer, Softball, Swimming, Volleyball
5th rowBasketball, Bowling, Tennis, Volleyball
ValueCountFrequency (%)
basketball 409
12.9%
volleyball 349
11.0%
track 340
10.7%
softball 312
9.8%
outdoor 182
 
5.7%
jv 180
 
5.7%
soccer 173
 
5.4%
171
 
5.4%
indoor 158
 
5.0%
tennis 148
 
4.7%
Other values (20) 754
23.7%
2023-12-09T22:17:30.536449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 3226
 
12.3%
2820
 
10.8%
a 2056
 
7.8%
o 2040
 
7.8%
, 1781
 
6.8%
r 1208
 
4.6%
b 1190
 
4.5%
e 1186
 
4.5%
t 1141
 
4.4%
s 1006
 
3.8%
Other values (29) 8547
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18248
69.6%
Uppercase Letter 3179
 
12.1%
Space Separator 2820
 
10.8%
Other Punctuation 1954
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 3226
17.7%
a 2056
11.3%
o 2040
11.2%
r 1208
 
6.6%
b 1190
 
6.5%
e 1186
 
6.5%
t 1141
 
6.3%
s 1006
 
5.5%
n 957
 
5.2%
c 778
 
4.3%
Other values (10) 3460
19.0%
Uppercase Letter
ValueCountFrequency (%)
B 548
17.2%
S 541
17.0%
V 529
16.6%
T 488
15.4%
C 297
9.3%
O 182
 
5.7%
J 180
 
5.7%
I 158
 
5.0%
H 71
 
2.2%
G 60
 
1.9%
Other values (5) 125
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 1781
91.1%
& 171
 
8.8%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
2820
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21427
81.8%
Common 4774
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 3226
15.1%
a 2056
 
9.6%
o 2040
 
9.5%
r 1208
 
5.6%
b 1190
 
5.6%
e 1186
 
5.5%
t 1141
 
5.3%
s 1006
 
4.7%
n 957
 
4.5%
c 778
 
3.6%
Other values (25) 6639
31.0%
Common
ValueCountFrequency (%)
2820
59.1%
, 1781
37.3%
& 171
 
3.6%
. 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26201
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 3226
 
12.3%
2820
 
10.8%
a 2056
 
7.8%
o 2040
 
7.8%
, 1781
 
6.8%
r 1208
 
4.6%
b 1190
 
4.5%
e 1186
 
4.5%
t 1141
 
4.4%
s 1006
 
3.8%
Other values (29) 8547
32.6%

psal_sports_coed
Text

MISSING 

Distinct62
Distinct (%)42.2%
Missing288
Missing (%)66.2%
Memory size19.8 KiB
2023-12-09T22:17:30.767739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length160
Median length43
Mean length17.04761905
Min length4

Characters and Unicode

Total characters2506
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)27.2%

Sample

1st rowCricket
2nd rowGolf
3rd rowSwimming, Wrestling
4th rowBowling, Cricket, Wrestling
5th rowCricket
ValueCountFrequency (%)
bowling 43
12.8%
track 30
 
8.9%
cricket 25
 
7.4%
cross 25
 
7.4%
country 25
 
7.4%
wrestling 23
 
6.8%
outdoor 21
 
6.2%
handball 18
 
5.4%
fencing 17
 
5.1%
swimming 14
 
4.2%
Other values (20) 95
28.3%
2023-12-09T22:17:31.187661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 201
 
8.0%
193
 
7.7%
o 193
 
7.7%
r 166
 
6.6%
l 164
 
6.5%
i 153
 
6.1%
t 120
 
4.8%
e 115
 
4.6%
, 107
 
4.3%
s 103
 
4.1%
Other values (28) 991
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1870
74.6%
Uppercase Letter 330
 
13.2%
Space Separator 193
 
7.7%
Other Punctuation 113
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 201
10.7%
o 193
10.3%
r 166
 
8.9%
l 164
 
8.8%
i 153
 
8.2%
t 120
 
6.4%
e 115
 
6.1%
s 103
 
5.5%
g 99
 
5.3%
c 95
 
5.1%
Other values (10) 461
24.7%
Uppercase Letter
ValueCountFrequency (%)
C 75
22.7%
B 53
16.1%
T 44
13.3%
S 23
 
7.0%
W 23
 
7.0%
O 21
 
6.4%
H 19
 
5.8%
F 19
 
5.8%
D 18
 
5.5%
G 12
 
3.6%
Other values (4) 23
 
7.0%
Other Punctuation
ValueCountFrequency (%)
, 107
94.7%
& 4
 
3.5%
. 2
 
1.8%
Space Separator
ValueCountFrequency (%)
193
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2200
87.8%
Common 306
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 201
 
9.1%
o 193
 
8.8%
r 166
 
7.5%
l 164
 
7.5%
i 153
 
7.0%
t 120
 
5.5%
e 115
 
5.2%
s 103
 
4.7%
g 99
 
4.5%
c 95
 
4.3%
Other values (24) 791
36.0%
Common
ValueCountFrequency (%)
193
63.1%
, 107
35.0%
& 4
 
1.3%
. 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 201
 
8.0%
193
 
7.7%
o 193
 
7.7%
r 166
 
6.6%
l 164
 
6.5%
i 153
 
6.1%
t 120
 
4.8%
e 115
 
4.6%
, 107
 
4.3%
s 103
 
4.1%
Other values (28) 991
39.5%

school_sports
Text

MISSING 

Distinct276
Distinct (%)92.9%
Missing138
Missing (%)31.7%
Memory size39.0 KiB
2023-12-09T22:17:31.576447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length372
Median length111
Mean length61.48148148
Min length6

Characters and Unicode

Total characters18260
Distinct characters73
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)90.6%

Sample

1st rowStep Team, Modern Dance, Hip Hop Dance
2nd rowBasketball Team
3rd rowBaseball, Basketball, Flag Football, Soccer, Softball, Volleyball
4th rowAGL Intramural Basketball, Soccer, Cheerleading
5th rowCheerleading, Teams: Dance, Step
ValueCountFrequency (%)
basketball 149
 
6.3%
soccer 92
 
3.9%
volleyball 80
 
3.4%
cheerleading 72
 
3.1%
football 69
 
2.9%
intramural 61
 
2.6%
baseball 59
 
2.5%
and 56
 
2.4%
track 55
 
2.3%
flag 55
 
2.3%
Other values (385) 1610
68.3%
2023-12-09T22:17:32.164198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2062
 
11.3%
l 1611
 
8.8%
a 1534
 
8.4%
e 1393
 
7.6%
o 965
 
5.3%
t 934
 
5.1%
r 829
 
4.5%
n 814
 
4.5%
s 798
 
4.4%
i 776
 
4.2%
Other values (63) 6544
35.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13253
72.6%
Space Separator 2062
 
11.3%
Uppercase Letter 1957
 
10.7%
Other Punctuation 877
 
4.8%
Dash Punctuation 47
 
0.3%
Decimal Number 28
 
0.2%
Open Punctuation 17
 
0.1%
Close Punctuation 17
 
0.1%
Initial Punctuation 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1611
12.2%
a 1534
11.6%
e 1393
10.5%
o 965
 
7.3%
t 934
 
7.0%
r 829
 
6.3%
n 814
 
6.1%
s 798
 
6.0%
i 776
 
5.9%
b 533
 
4.0%
Other values (16) 3066
23.1%
Uppercase Letter
ValueCountFrequency (%)
S 313
16.0%
B 293
15.0%
C 210
10.7%
F 197
10.1%
T 168
8.6%
V 96
 
4.9%
A 86
 
4.4%
I 74
 
3.8%
G 73
 
3.7%
W 62
 
3.2%
Other values (15) 385
19.7%
Other Punctuation
ValueCountFrequency (%)
, 751
85.6%
. 40
 
4.6%
; 31
 
3.5%
: 30
 
3.4%
& 12
 
1.4%
/ 6
 
0.7%
' 4
 
0.5%
! 3
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 6
21.4%
1 5
17.9%
0 4
14.3%
3 4
14.3%
7 3
10.7%
9 3
10.7%
8 2
 
7.1%
5 1
 
3.6%
Space Separator
ValueCountFrequency (%)
2062
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15210
83.3%
Common 3050
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1611
 
10.6%
a 1534
 
10.1%
e 1393
 
9.2%
o 965
 
6.3%
t 934
 
6.1%
r 829
 
5.5%
n 814
 
5.4%
s 798
 
5.2%
i 776
 
5.1%
b 533
 
3.5%
Other values (41) 5023
33.0%
Common
ValueCountFrequency (%)
2062
67.6%
, 751
 
24.6%
- 47
 
1.5%
. 40
 
1.3%
; 31
 
1.0%
: 30
 
1.0%
( 17
 
0.6%
) 17
 
0.6%
& 12
 
0.4%
/ 6
 
0.2%
Other values (12) 37
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18258
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2062
 
11.3%
l 1611
 
8.8%
a 1534
 
8.4%
e 1393
 
7.6%
o 965
 
5.3%
t 934
 
5.1%
r 829
 
4.5%
n 814
 
4.5%
s 798
 
4.4%
i 776
 
4.3%
Other values (61) 6542
35.8%
Punctuation
ValueCountFrequency (%)
“ 1
50.0%
” 1
50.0%

partner_cbo
Text

MISSING 

Distinct346
Distinct (%)97.7%
Missing81
Missing (%)18.6%
Memory size68.5 KiB
2023-12-09T22:17:32.536261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length685
Median length197
Mean length119.0112994
Min length6

Characters and Unicode

Total characters42130
Distinct characters81
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique339 ?
Unique (%)95.8%

Sample

1st rowConey Island Generation Gap
2nd rowAchieving Change in our Neighborhood (Teen ACTION) St.Nicks Alliance, New York City College of Technology – STEM Robotics, Fresh Prep and New York Hall of Science
3rd rowLincoln Center for the Performing Arts
4th rowHenry Street Settlement, Peer Health Exchange, Generation Citizen, My School-My Community
5th rowBronx Arts Ensemble, Korea Tae Kwon Do
ValueCountFrequency (%)
the 139
 
2.5%
for 128
 
2.3%
and 116
 
2.1%
new 114
 
2.0%
of 109
 
1.9%
center 105
 
1.9%
york 98
 
1.7%
program 89
 
1.6%
community 82
 
1.5%
college 71
 
1.3%
Other values (1513) 4602
81.4%
2023-12-09T22:17:33.090269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5299
 
12.6%
e 3598
 
8.5%
o 2715
 
6.4%
n 2521
 
6.0%
i 2463
 
5.8%
r 2454
 
5.8%
t 2371
 
5.6%
a 2204
 
5.2%
s 1604
 
3.8%
l 1330
 
3.2%
Other values (71) 15571
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29115
69.1%
Uppercase Letter 5836
 
13.9%
Space Separator 5299
 
12.6%
Other Punctuation 1385
 
3.3%
Close Punctuation 153
 
0.4%
Open Punctuation 153
 
0.4%
Decimal Number 89
 
0.2%
Dash Punctuation 77
 
0.2%
Final Punctuation 18
 
< 0.1%
Initial Punctuation 2
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3598
12.4%
o 2715
 
9.3%
n 2521
 
8.7%
i 2463
 
8.5%
r 2454
 
8.4%
t 2371
 
8.1%
a 2204
 
7.6%
s 1604
 
5.5%
l 1330
 
4.6%
c 995
 
3.4%
Other values (16) 6860
23.6%
Uppercase Letter
ValueCountFrequency (%)
C 861
14.8%
S 588
 
10.1%
A 547
 
9.4%
P 407
 
7.0%
Y 296
 
5.1%
N 275
 
4.7%
E 259
 
4.4%
M 252
 
4.3%
H 252
 
4.3%
B 252
 
4.3%
Other values (16) 1847
31.6%
Decimal Number
ValueCountFrequency (%)
1 20
22.5%
0 12
13.5%
2 11
12.4%
4 11
12.4%
6 9
10.1%
3 9
10.1%
9 5
 
5.6%
5 5
 
5.6%
7 4
 
4.5%
8 3
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 1052
76.0%
. 140
 
10.1%
; 70
 
5.1%
' 55
 
4.0%
& 23
 
1.7%
/ 22
 
1.6%
: 17
 
1.2%
@ 3
 
0.2%
! 3
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 75
97.4%
– 2
 
2.6%
Final Punctuation
ValueCountFrequency (%)
’ 17
94.4%
” 1
 
5.6%
Space Separator
ValueCountFrequency (%)
5299
100.0%
Close Punctuation
ValueCountFrequency (%)
) 153
100.0%
Open Punctuation
ValueCountFrequency (%)
( 153
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34951
83.0%
Common 7179
 
17.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3598
 
10.3%
o 2715
 
7.8%
n 2521
 
7.2%
i 2463
 
7.0%
r 2454
 
7.0%
t 2371
 
6.8%
a 2204
 
6.3%
s 1604
 
4.6%
l 1330
 
3.8%
c 995
 
2.8%
Other values (42) 12696
36.3%
Common
ValueCountFrequency (%)
5299
73.8%
, 1052
 
14.7%
) 153
 
2.1%
( 153
 
2.1%
. 140
 
2.0%
- 75
 
1.0%
; 70
 
1.0%
' 55
 
0.8%
& 23
 
0.3%
/ 22
 
0.3%
Other values (19) 137
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42108
99.9%
Punctuation 22
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5299
 
12.6%
e 3598
 
8.5%
o 2715
 
6.4%
n 2521
 
6.0%
i 2463
 
5.8%
r 2454
 
5.8%
t 2371
 
5.6%
a 2204
 
5.2%
s 1604
 
3.8%
l 1330
 
3.2%
Other values (67) 15549
36.9%
Punctuation
ValueCountFrequency (%)
’ 17
77.3%
– 2
 
9.1%
“ 2
 
9.1%
” 1
 
4.5%

partner_hospital
Text

MISSING 

Distinct175
Distinct (%)89.3%
Missing239
Missing (%)54.9%
Memory size31.1 KiB
2023-12-09T22:17:33.431048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length683
Median length98
Mean length61.58163265
Min length10

Characters and Unicode

Total characters12070
Distinct characters62
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)82.1%

Sample

1st rowJamaica Hospital Medical Center, Peninsula Hospital Center
2nd rowSoundview Health Center, Bronx Lebanon Hospital Center, Montefiore Medical Center
3rd rowMount Sinai Medical Center
4th rowElmhurst Hospital
5th rowJamaica Hospital Center (on-site facility)
ValueCountFrequency (%)
center 167
 
10.7%
hospital 163
 
10.4%
medical 107
 
6.8%
health 53
 
3.4%
and 39
 
2.5%
clinic 36
 
2.3%
new 35
 
2.2%
montefiore 32
 
2.0%
island 28
 
1.8%
sinai 23
 
1.5%
Other values (314) 882
56.4%
2023-12-09T22:17:33.958344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1369
 
11.3%
e 1236
 
10.2%
i 829
 
6.9%
t 821
 
6.8%
n 777
 
6.4%
a 739
 
6.1%
o 736
 
6.1%
l 651
 
5.4%
r 626
 
5.2%
s 509
 
4.2%
Other values (52) 3777
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8777
72.7%
Uppercase Letter 1540
 
12.8%
Space Separator 1369
 
11.3%
Other Punctuation 236
 
2.0%
Dash Punctuation 68
 
0.6%
Close Punctuation 38
 
0.3%
Open Punctuation 38
 
0.3%
Final Punctuation 3
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1236
14.1%
i 829
9.4%
t 821
9.4%
n 777
8.9%
a 739
8.4%
o 736
8.4%
l 651
7.4%
r 626
 
7.1%
s 509
 
5.8%
c 266
 
3.0%
Other values (14) 1587
18.1%
Uppercase Letter
ValueCountFrequency (%)
C 282
18.3%
H 263
17.1%
M 215
14.0%
S 127
8.2%
N 81
 
5.3%
I 61
 
4.0%
L 59
 
3.8%
Y 57
 
3.7%
P 48
 
3.1%
B 42
 
2.7%
Other values (14) 305
19.8%
Other Punctuation
ValueCountFrequency (%)
, 167
70.8%
. 34
 
14.4%
' 16
 
6.8%
/ 8
 
3.4%
& 7
 
3.0%
; 2
 
0.8%
: 2
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 67
98.5%
– 1
 
1.5%
Space Separator
ValueCountFrequency (%)
1369
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%
Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10317
85.5%
Common 1753
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1236
 
12.0%
i 829
 
8.0%
t 821
 
8.0%
n 777
 
7.5%
a 739
 
7.2%
o 736
 
7.1%
l 651
 
6.3%
r 626
 
6.1%
s 509
 
4.9%
C 282
 
2.7%
Other values (38) 3111
30.2%
Common
ValueCountFrequency (%)
1369
78.1%
, 167
 
9.5%
- 67
 
3.8%
) 38
 
2.2%
( 38
 
2.2%
. 34
 
1.9%
' 16
 
0.9%
/ 8
 
0.5%
& 7
 
0.4%
’ 3
 
0.2%
Other values (4) 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12066
> 99.9%
Punctuation 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1369
 
11.3%
e 1236
 
10.2%
i 829
 
6.9%
t 821
 
6.8%
n 777
 
6.4%
a 739
 
6.1%
o 736
 
6.1%
l 651
 
5.4%
r 626
 
5.2%
s 509
 
4.2%
Other values (50) 3773
31.3%
Punctuation
ValueCountFrequency (%)
’ 3
75.0%
– 1
 
25.0%

partner_highered
Text

MISSING 

Distinct344
Distinct (%)91.0%
Missing57
Missing (%)13.1%
Memory size70.9 KiB
2023-12-09T22:17:34.319982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length834
Median length205
Mean length117.2724868
Min length12

Characters and Unicode

Total characters44329
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)86.8%

Sample

1st rowYork College, Brooklyn College, St. John's College
2nd rowCity Tech, Kingsborough Early College Secondary School, City University of New Jersey
3rd rowMedgar Evers College
4th rowHostos Community College, Monroe College, Lehman College
5th rowThe Cooper Union for the Advancement of Science and Art, Skidmore College, Sophie Davis School of Biomedical Education, New York University School of Medicine
ValueCountFrequency (%)
college 942
 
15.8%
university 592
 
9.9%
of 354
 
5.9%
york 291
 
4.9%
new 287
 
4.8%
community 171
 
2.9%
city 143
 
2.4%
the 108
 
1.8%
columbia 83
 
1.4%
institute 79
 
1.3%
Other values (630) 2921
48.9%
2023-12-09T22:17:34.849407image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5595
 
12.6%
e 4445
 
10.0%
o 3547
 
8.0%
l 2660
 
6.0%
i 2397
 
5.4%
n 2322
 
5.2%
r 2142
 
4.8%
t 2096
 
4.7%
C 1573
 
3.5%
s 1470
 
3.3%
Other values (57) 16082
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31131
70.2%
Uppercase Letter 5799
 
13.1%
Space Separator 5595
 
12.6%
Other Punctuation 1454
 
3.3%
Close Punctuation 145
 
0.3%
Open Punctuation 145
 
0.3%
Dash Punctuation 36
 
0.1%
Final Punctuation 21
 
< 0.1%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4445
14.3%
o 3547
11.4%
l 2660
 
8.5%
i 2397
 
7.7%
n 2322
 
7.5%
r 2142
 
6.9%
t 2096
 
6.7%
s 1470
 
4.7%
a 1426
 
4.6%
g 1390
 
4.5%
Other values (16) 7236
23.2%
Uppercase Letter
ValueCountFrequency (%)
C 1573
27.1%
U 772
13.3%
N 501
 
8.6%
Y 451
 
7.8%
S 352
 
6.1%
T 279
 
4.8%
B 231
 
4.0%
M 186
 
3.2%
L 177
 
3.1%
J 166
 
2.9%
Other values (14) 1111
19.2%
Other Punctuation
ValueCountFrequency (%)
, 1196
82.3%
. 112
 
7.7%
; 68
 
4.7%
' 46
 
3.2%
: 14
 
1.0%
/ 12
 
0.8%
& 3
 
0.2%
@ 3
 
0.2%
Decimal Number
ValueCountFrequency (%)
9 1
33.3%
1 1
33.3%
2 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 35
97.2%
– 1
 
2.8%
Space Separator
ValueCountFrequency (%)
5595
100.0%
Close Punctuation
ValueCountFrequency (%)
) 145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 145
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36930
83.3%
Common 7399
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4445
 
12.0%
o 3547
 
9.6%
l 2660
 
7.2%
i 2397
 
6.5%
n 2322
 
6.3%
r 2142
 
5.8%
t 2096
 
5.7%
C 1573
 
4.3%
s 1470
 
4.0%
a 1426
 
3.9%
Other values (40) 12852
34.8%
Common
ValueCountFrequency (%)
5595
75.6%
, 1196
 
16.2%
) 145
 
2.0%
( 145
 
2.0%
. 112
 
1.5%
; 68
 
0.9%
' 46
 
0.6%
- 35
 
0.5%
’ 21
 
0.3%
: 14
 
0.2%
Other values (7) 22
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44307
> 99.9%
Punctuation 22
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5595
 
12.6%
e 4445
 
10.0%
o 3547
 
8.0%
l 2660
 
6.0%
i 2397
 
5.4%
n 2322
 
5.2%
r 2142
 
4.8%
t 2096
 
4.7%
C 1573
 
3.6%
s 1470
 
3.3%
Other values (55) 16060
36.2%
Punctuation
ValueCountFrequency (%)
’ 21
95.5%
– 1
 
4.5%

partner_cultural
Text

MISSING 

Distinct302
Distinct (%)99.0%
Missing130
Missing (%)29.9%
Memory size58.6 KiB
2023-12-09T22:17:35.223131image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length683
Median length178
Mean length117.6327869
Min length5

Characters and Unicode

Total characters35878
Distinct characters78
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)98.0%

Sample

1st rowMuseum of the Moving Image, New York Public Library
2nd rowNoel Pointer School of Music
3rd rowChilean Consulate, Materials for the Arts
4th rowLincoln Center for the Performing Arts, American Ballet Theater, Carnegie Hall, New York Philharmonic, Drama Desk, Metropolitan Opera, Interschool Orchestras of New York, New York Youth Symphony
5th rowAbrons Art Center (provides drama instruction)
ValueCountFrequency (%)
of 237
 
4.7%
the 221
 
4.4%
museum 201
 
4.0%
arts 157
 
3.1%
center 129
 
2.5%
art 116
 
2.3%
theatre 100
 
2.0%
for 94
 
1.9%
theater 90
 
1.8%
new 86
 
1.7%
Other values (1067) 3630
71.7%
2023-12-09T22:17:35.782038image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4757
 
13.3%
e 3099
 
8.6%
r 2319
 
6.5%
o 2291
 
6.4%
t 2198
 
6.1%
a 2063
 
5.8%
n 1980
 
5.5%
i 1619
 
4.5%
s 1291
 
3.6%
l 1154
 
3.2%
Other values (68) 13107
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24959
69.6%
Space Separator 4757
 
13.3%
Uppercase Letter 4675
 
13.0%
Other Punctuation 1154
 
3.2%
Open Punctuation 116
 
0.3%
Close Punctuation 115
 
0.3%
Dash Punctuation 56
 
0.2%
Decimal Number 38
 
0.1%
Final Punctuation 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3099
12.4%
r 2319
 
9.3%
o 2291
 
9.2%
t 2198
 
8.8%
a 2063
 
8.3%
n 1980
 
7.9%
i 1619
 
6.5%
s 1291
 
5.2%
l 1154
 
4.6%
u 1103
 
4.4%
Other values (18) 5842
23.4%
Uppercase Letter
ValueCountFrequency (%)
A 626
13.4%
M 517
11.1%
C 509
10.9%
T 429
 
9.2%
S 322
 
6.9%
P 244
 
5.2%
N 213
 
4.6%
B 209
 
4.5%
E 179
 
3.8%
F 166
 
3.6%
Other values (16) 1261
27.0%
Other Punctuation
ValueCountFrequency (%)
, 998
86.5%
. 74
 
6.4%
; 29
 
2.5%
' 27
 
2.3%
: 9
 
0.8%
/ 9
 
0.8%
& 5
 
0.4%
! 2
 
0.2%
@ 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 13
34.2%
9 7
18.4%
0 6
15.8%
1 6
15.8%
4 2
 
5.3%
5 2
 
5.3%
6 1
 
2.6%
8 1
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 55
98.2%
– 1
 
1.8%
Space Separator
ValueCountFrequency (%)
4757
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29634
82.6%
Common 6244
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3099
 
10.5%
r 2319
 
7.8%
o 2291
 
7.7%
t 2198
 
7.4%
a 2063
 
7.0%
n 1980
 
6.7%
i 1619
 
5.5%
s 1291
 
4.4%
l 1154
 
3.9%
u 1103
 
3.7%
Other values (44) 10517
35.5%
Common
ValueCountFrequency (%)
4757
76.2%
, 998
 
16.0%
( 116
 
1.9%
) 115
 
1.8%
. 74
 
1.2%
- 55
 
0.9%
; 29
 
0.5%
' 27
 
0.4%
2 13
 
0.2%
: 9
 
0.1%
Other values (14) 51
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35866
> 99.9%
Punctuation 8
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4757
 
13.3%
e 3099
 
8.6%
r 2319
 
6.5%
o 2291
 
6.4%
t 2198
 
6.1%
a 2063
 
5.8%
n 1980
 
5.5%
i 1619
 
4.5%
s 1291
 
3.6%
l 1154
 
3.2%
Other values (64) 13095
36.5%
Punctuation
ValueCountFrequency (%)
’ 7
87.5%
– 1
 
12.5%
None
ValueCountFrequency (%)
ñ 3
75.0%
é 1
 
25.0%

partner_nonprofit
Text

MISSING 

Distinct276
Distinct (%)92.9%
Missing138
Missing (%)31.7%
Memory size50.7 KiB
2023-12-09T22:17:36.183475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length996
Median length146
Mean length93.18855219
Min length3

Characters and Unicode

Total characters27677
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique268 ?
Unique (%)90.2%

Sample

1st rowQueens District Attorney, Sports and Arts Foundation, CMS
2nd rowInstitute for Student Achievement
3rd rowHip-Hop 4 Life, Urban Arts, and St. Nicks Alliance
4th rowNetwork for Teaching Entrepreneurship (NFTE), BISCEP (The Leadership Program), New York Cares, Institute for Student Achievement (ISA), PENCIL
5th rowJunior Achievement, Red Cross, United Nations Association, American Cancer Society
ValueCountFrequency (%)
for 166
 
4.4%
new 113
 
3.0%
the 108
 
2.9%
york 75
 
2.0%
of 74
 
2.0%
foundation 67
 
1.8%
and 52
 
1.4%
schools 50
 
1.3%
center 47
 
1.3%
public 42
 
1.1%
Other values (1055) 2944
78.8%
2023-12-09T22:17:36.769039image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3442
 
12.4%
e 2263
 
8.2%
o 1898
 
6.9%
n 1714
 
6.2%
r 1632
 
5.9%
i 1609
 
5.8%
t 1548
 
5.6%
a 1422
 
5.1%
s 1072
 
3.9%
l 824
 
3.0%
Other values (66) 10253
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19055
68.8%
Uppercase Letter 3979
 
14.4%
Space Separator 3442
 
12.4%
Other Punctuation 863
 
3.1%
Open Punctuation 119
 
0.4%
Close Punctuation 119
 
0.4%
Dash Punctuation 57
 
0.2%
Decimal Number 30
 
0.1%
Final Punctuation 12
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2263
11.9%
o 1898
10.0%
n 1714
 
9.0%
r 1632
 
8.6%
i 1609
 
8.4%
t 1548
 
8.1%
a 1422
 
7.5%
s 1072
 
5.6%
l 824
 
4.3%
c 732
 
3.8%
Other values (16) 4341
22.8%
Uppercase Letter
ValueCountFrequency (%)
C 513
12.9%
A 395
 
9.9%
S 345
 
8.7%
N 312
 
7.8%
P 259
 
6.5%
E 221
 
5.6%
F 186
 
4.7%
I 180
 
4.5%
T 168
 
4.2%
Y 164
 
4.1%
Other values (16) 1236
31.1%
Other Punctuation
ValueCountFrequency (%)
, 725
84.0%
. 57
 
6.6%
' 27
 
3.1%
; 14
 
1.6%
/ 13
 
1.5%
& 13
 
1.5%
! 7
 
0.8%
: 6
 
0.7%
% 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 10
33.3%
1 6
20.0%
2 4
 
13.3%
3 2
 
6.7%
8 2
 
6.7%
5 2
 
6.7%
6 2
 
6.7%
9 1
 
3.3%
4 1
 
3.3%
Space Separator
ValueCountFrequency (%)
3442
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 12
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23034
83.2%
Common 4643
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2263
 
9.8%
o 1898
 
8.2%
n 1714
 
7.4%
r 1632
 
7.1%
i 1609
 
7.0%
t 1548
 
6.7%
a 1422
 
6.2%
s 1072
 
4.7%
l 824
 
3.6%
c 732
 
3.2%
Other values (42) 8320
36.1%
Common
ValueCountFrequency (%)
3442
74.1%
, 725
 
15.6%
( 119
 
2.6%
) 119
 
2.6%
. 57
 
1.2%
- 57
 
1.2%
' 27
 
0.6%
; 14
 
0.3%
/ 13
 
0.3%
& 13
 
0.3%
Other values (14) 57
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27664
> 99.9%
Punctuation 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3442
 
12.4%
e 2263
 
8.2%
o 1898
 
6.9%
n 1714
 
6.2%
r 1632
 
5.9%
i 1609
 
5.8%
t 1548
 
5.6%
a 1422
 
5.1%
s 1072
 
3.9%
l 824
 
3.0%
Other values (64) 10240
37.0%
Punctuation
ValueCountFrequency (%)
’ 12
92.3%
‘ 1
 
7.7%

partner_corporate
Text

MISSING 

Distinct195
Distinct (%)98.5%
Missing237
Missing (%)54.5%
Memory size31.9 KiB
2023-12-09T22:17:37.158225image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length444
Median length137
Mean length65.68181818
Min length6

Characters and Unicode

Total characters13005
Distinct characters72
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)97.0%

Sample

1st rowReplications, Inc.
2nd rowFilm Life, Inc., SONY Wonder Tech
3rd rowSony Music, Warner Music Group, Capital Cities ABC, The Walt Disney Company
4th rowJones Day Law Firm
5th rowBlackstone Group
ValueCountFrequency (%)
45
 
2.5%
the 34
 
1.9%
of 30
 
1.7%
inc 28
 
1.6%
and 28
 
1.6%
llp 27
 
1.5%
new 25
 
1.4%
york 20
 
1.1%
foundation 17
 
1.0%
construction 17
 
1.0%
Other values (899) 1501
84.7%
2023-12-09T22:17:37.727732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1574
 
12.1%
e 962
 
7.4%
n 855
 
6.6%
o 841
 
6.5%
a 775
 
6.0%
i 773
 
5.9%
r 760
 
5.8%
t 669
 
5.1%
s 552
 
4.2%
, 428
 
3.3%
Other values (62) 4816
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8777
67.5%
Uppercase Letter 1960
 
15.1%
Space Separator 1574
 
12.1%
Other Punctuation 593
 
4.6%
Open Punctuation 27
 
0.2%
Close Punctuation 27
 
0.2%
Dash Punctuation 23
 
0.2%
Decimal Number 19
 
0.1%
Final Punctuation 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 962
11.0%
n 855
9.7%
o 841
9.6%
a 775
8.8%
i 773
8.8%
r 760
8.7%
t 669
 
7.6%
s 552
 
6.3%
l 424
 
4.8%
c 328
 
3.7%
Other values (17) 1838
20.9%
Uppercase Letter
ValueCountFrequency (%)
C 223
 
11.4%
A 154
 
7.9%
S 152
 
7.8%
T 136
 
6.9%
M 129
 
6.6%
L 126
 
6.4%
P 118
 
6.0%
B 114
 
5.8%
I 97
 
4.9%
N 95
 
4.8%
Other values (16) 616
31.4%
Other Punctuation
ValueCountFrequency (%)
, 428
72.2%
. 61
 
10.3%
& 45
 
7.6%
; 31
 
5.2%
' 16
 
2.7%
/ 9
 
1.5%
: 3
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 6
31.6%
1 5
26.3%
2 3
15.8%
3 3
15.8%
9 1
 
5.3%
5 1
 
5.3%
Space Separator
ValueCountFrequency (%)
1574
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10737
82.6%
Common 2268
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 962
 
9.0%
n 855
 
8.0%
o 841
 
7.8%
a 775
 
7.2%
i 773
 
7.2%
r 760
 
7.1%
t 669
 
6.2%
s 552
 
5.1%
l 424
 
3.9%
c 328
 
3.1%
Other values (43) 3798
35.4%
Common
ValueCountFrequency (%)
1574
69.4%
, 428
 
18.9%
. 61
 
2.7%
& 45
 
2.0%
; 31
 
1.4%
( 27
 
1.2%
) 27
 
1.2%
- 23
 
1.0%
' 16
 
0.7%
/ 9
 
0.4%
Other values (9) 27
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12998
99.9%
Punctuation 4
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1574
 
12.1%
e 962
 
7.4%
n 855
 
6.6%
o 841
 
6.5%
a 775
 
6.0%
i 773
 
5.9%
r 760
 
5.8%
t 669
 
5.1%
s 552
 
4.2%
, 428
 
3.3%
Other values (60) 4809
37.0%
Punctuation
ValueCountFrequency (%)
’ 4
100.0%
None
ValueCountFrequency (%)
é 3
100.0%

partner_financial
Text

MISSING 

Distinct64
Distinct (%)88.9%
Missing363
Missing (%)83.4%
Memory size18.7 KiB
2023-12-09T22:17:38.041229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length493
Median length60
Mean length44.77777778
Min length8

Characters and Unicode

Total characters3224
Distinct characters58
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)80.6%

Sample

1st rowCitibank
2nd rowRidgewood Savings Bank
3rd rowBuilding Readiness in Today’s Entrepreneurs (BRITE), Mission I'M Possible
4th rowWorking in Support of Education (W!SE)- Financial Literacy Program
5th rowCapital One
ValueCountFrequency (%)
bank 38
 
8.2%
of 19
 
4.1%
chase 17
 
3.7%
york 12
 
2.6%
new 12
 
2.6%
morgan 11
 
2.4%
federal 11
 
2.4%
10
 
2.2%
capital 9
 
2.0%
reserve 9
 
2.0%
Other values (166) 313
67.9%
2023-12-09T22:17:38.523080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
389
 
12.1%
e 263
 
8.2%
a 244
 
7.6%
n 235
 
7.3%
i 189
 
5.9%
r 183
 
5.7%
o 172
 
5.3%
t 144
 
4.5%
s 119
 
3.7%
c 84
 
2.6%
Other values (48) 1202
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2201
68.3%
Uppercase Letter 507
 
15.7%
Space Separator 389
 
12.1%
Other Punctuation 96
 
3.0%
Close Punctuation 12
 
0.4%
Open Punctuation 12
 
0.4%
Dash Punctuation 6
 
0.2%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 263
11.9%
a 244
11.1%
n 235
10.7%
i 189
 
8.6%
r 183
 
8.3%
o 172
 
7.8%
t 144
 
6.5%
s 119
 
5.4%
c 84
 
3.8%
l 69
 
3.1%
Other values (15) 499
22.7%
Uppercase Letter
ValueCountFrequency (%)
C 72
14.2%
B 64
12.6%
S 49
 
9.7%
M 35
 
6.9%
A 34
 
6.7%
F 33
 
6.5%
P 29
 
5.7%
R 25
 
4.9%
I 22
 
4.3%
E 21
 
4.1%
Other values (12) 123
24.3%
Other Punctuation
ValueCountFrequency (%)
, 72
75.0%
& 10
 
10.4%
. 8
 
8.3%
' 3
 
3.1%
! 2
 
2.1%
; 1
 
1.0%
Space Separator
ValueCountFrequency (%)
389
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2708
84.0%
Common 516
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 263
 
9.7%
a 244
 
9.0%
n 235
 
8.7%
i 189
 
7.0%
r 183
 
6.8%
o 172
 
6.4%
t 144
 
5.3%
s 119
 
4.4%
c 84
 
3.1%
C 72
 
2.7%
Other values (37) 1003
37.0%
Common
ValueCountFrequency (%)
389
75.4%
, 72
 
14.0%
) 12
 
2.3%
( 12
 
2.3%
& 10
 
1.9%
. 8
 
1.6%
- 6
 
1.2%
' 3
 
0.6%
! 2
 
0.4%
’ 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3223
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
389
 
12.1%
e 263
 
8.2%
a 244
 
7.6%
n 235
 
7.3%
i 189
 
5.9%
r 183
 
5.7%
o 172
 
5.3%
t 144
 
4.5%
s 119
 
3.7%
c 84
 
2.6%
Other values (47) 1201
37.3%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

partner_other
Text

MISSING 

Distinct186
Distinct (%)98.9%
Missing247
Missing (%)56.8%
Memory size36.9 KiB
2023-12-09T22:17:38.937622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length692
Median length125
Mean length85.40957447
Min length4

Characters and Unicode

Total characters16057
Distinct characters76
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)97.9%

Sample

1st rowNew York Road Runners Foundation (NYRRF)
2nd rowiLearnNYC
3rd rowYoung Audiences Artist-in-Residence Program (students use media in an interactive way as a means of expression and research)
4th rowThe New York Times
5th rowCo-op Tech
ValueCountFrequency (%)
of 64
 
2.9%
new 62
 
2.8%
york 59
 
2.7%
and 54
 
2.4%
the 52
 
2.3%
for 42
 
1.9%
school 32
 
1.4%
city 27
 
1.2%
office 27
 
1.2%
program 26
 
1.2%
Other values (934) 1769
79.9%
2023-12-09T22:17:39.579455image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2026
 
12.6%
e 1345
 
8.4%
o 1111
 
6.9%
n 1006
 
6.3%
t 957
 
6.0%
r 946
 
5.9%
i 922
 
5.7%
a 914
 
5.7%
s 640
 
4.0%
l 514
 
3.2%
Other values (66) 5676
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11431
71.2%
Space Separator 2026
 
12.6%
Uppercase Letter 1972
 
12.3%
Other Punctuation 421
 
2.6%
Close Punctuation 59
 
0.4%
Open Punctuation 59
 
0.4%
Decimal Number 37
 
0.2%
Dash Punctuation 36
 
0.2%
Final Punctuation 16
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1345
11.8%
o 1111
9.7%
n 1006
 
8.8%
t 957
 
8.4%
r 946
 
8.3%
i 922
 
8.1%
a 914
 
8.0%
s 640
 
5.6%
l 514
 
4.5%
c 468
 
4.1%
Other values (16) 2608
22.8%
Uppercase Letter
ValueCountFrequency (%)
C 260
13.2%
S 204
 
10.3%
A 171
 
8.7%
N 146
 
7.4%
P 122
 
6.2%
Y 107
 
5.4%
T 99
 
5.0%
E 93
 
4.7%
B 89
 
4.5%
I 78
 
4.0%
Other values (15) 603
30.6%
Other Punctuation
ValueCountFrequency (%)
, 310
73.6%
. 56
 
13.3%
' 22
 
5.2%
: 9
 
2.1%
; 7
 
1.7%
& 7
 
1.7%
/ 7
 
1.7%
! 2
 
0.5%
@ 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 10
27.0%
2 7
18.9%
3 5
13.5%
0 5
13.5%
6 3
 
8.1%
8 3
 
8.1%
4 2
 
5.4%
5 1
 
2.7%
7 1
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 34
94.4%
— 1
 
2.8%
– 1
 
2.8%
Space Separator
ValueCountFrequency (%)
2026
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13403
83.5%
Common 2654
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1345
 
10.0%
o 1111
 
8.3%
n 1006
 
7.5%
t 957
 
7.1%
r 946
 
7.1%
i 922
 
6.9%
a 914
 
6.8%
s 640
 
4.8%
l 514
 
3.8%
c 468
 
3.5%
Other values (41) 4580
34.2%
Common
ValueCountFrequency (%)
2026
76.3%
, 310
 
11.7%
) 59
 
2.2%
( 59
 
2.2%
. 56
 
2.1%
- 34
 
1.3%
' 22
 
0.8%
’ 16
 
0.6%
1 10
 
0.4%
: 9
 
0.3%
Other values (15) 53
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16039
99.9%
Punctuation 18
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2026
 
12.6%
e 1345
 
8.4%
o 1111
 
6.9%
n 1006
 
6.3%
t 957
 
6.0%
r 946
 
5.9%
i 922
 
5.7%
a 914
 
5.7%
s 640
 
4.0%
l 514
 
3.2%
Other values (63) 5658
35.3%
Punctuation
ValueCountFrequency (%)
’ 16
88.9%
— 1
 
5.6%
– 1
 
5.6%

addtl_info1
Text

MISSING 

Distinct335
Distinct (%)94.6%
Missing81
Missing (%)18.6%
Memory size102.7 KiB
2023-12-09T22:17:40.013043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1165
Median length297
Mean length197.7118644
Min length1

Characters and Unicode

Total characters69990
Distinct characters77
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique330 ?
Unique (%)93.2%

Sample

1st rowUniform Required: plain white collared shirt, black pants/skirt, FDA tie/FDA scarf, black shoes
2nd rowOur school requires completion of a Common Core Learning Standards Skills Portfolio for Assessment in every class
3rd rowDress Code Required: solid white shirt/blouse, navy blue blazer, gray pants/skirt, navy blue tie/scarf, black dress shoes, Participation in our 2-day FDA IV Prep Institute (Orientation) is required for incoming students, Extended Day Program
4th rowAll students are individually programmed (based on academic needs), Incoming 9th grade students attend our Summer Orientation Session, All students are assigned to a small Student Learning Community that meets twice a week, College preparation begins in 9th grade and continues through 12th grade; this preparation includes College Trips (in-state, out-of-state, trade schools), College Fairs, College Workshops
5th rowChancellor’s Arts Endorsed Diploma
ValueCountFrequency (%)
required 298
 
3.0%
and 240
 
2.4%
school 231
 
2.3%
or 199
 
2.0%
black 195
 
1.9%
for 191
 
1.9%
shirt 167
 
1.7%
the 154
 
1.5%
dress 153
 
1.5%
uniform 146
 
1.5%
Other values (1541) 8027
80.3%
2023-12-09T22:17:40.646743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9725
13.9%
e 6235
 
8.9%
r 4804
 
6.9%
o 4543
 
6.5%
s 4027
 
5.8%
t 4027
 
5.8%
a 3919
 
5.6%
i 3665
 
5.2%
n 3396
 
4.9%
l 2482
 
3.5%
Other values (67) 23167
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 53649
76.7%
Space Separator 9725
 
13.9%
Uppercase Letter 3428
 
4.9%
Other Punctuation 2054
 
2.9%
Decimal Number 545
 
0.8%
Dash Punctuation 306
 
0.4%
Close Punctuation 122
 
0.2%
Open Punctuation 121
 
0.2%
Final Punctuation 37
 
0.1%
Initial Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6235
11.6%
r 4804
 
9.0%
o 4543
 
8.5%
s 4027
 
7.5%
t 4027
 
7.5%
a 3919
 
7.3%
i 3665
 
6.8%
n 3396
 
6.3%
l 2482
 
4.6%
d 2420
 
4.5%
Other values (16) 14131
26.3%
Uppercase Letter
ValueCountFrequency (%)
S 469
13.7%
A 343
10.0%
P 342
10.0%
C 339
9.9%
R 315
9.2%
D 269
 
7.8%
E 215
 
6.3%
O 152
 
4.4%
U 142
 
4.1%
T 116
 
3.4%
Other values (15) 726
21.2%
Decimal Number
ValueCountFrequency (%)
1 126
23.1%
0 114
20.9%
2 71
13.0%
9 48
 
8.8%
5 45
 
8.3%
3 44
 
8.1%
4 42
 
7.7%
8 33
 
6.1%
6 14
 
2.6%
7 8
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 1131
55.1%
: 304
 
14.8%
/ 297
 
14.5%
. 141
 
6.9%
; 108
 
5.3%
' 58
 
2.8%
& 13
 
0.6%
@ 2
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 286
93.5%
– 20
 
6.5%
Final Punctuation
ValueCountFrequency (%)
’ 34
91.9%
” 3
 
8.1%
Space Separator
ValueCountFrequency (%)
9725
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 57077
81.6%
Common 12913
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6235
 
10.9%
r 4804
 
8.4%
o 4543
 
8.0%
s 4027
 
7.1%
t 4027
 
7.1%
a 3919
 
6.9%
i 3665
 
6.4%
n 3396
 
5.9%
l 2482
 
4.3%
d 2420
 
4.2%
Other values (41) 17559
30.8%
Common
ValueCountFrequency (%)
9725
75.3%
, 1131
 
8.8%
: 304
 
2.4%
/ 297
 
2.3%
- 286
 
2.2%
. 141
 
1.1%
1 126
 
1.0%
) 122
 
0.9%
( 121
 
0.9%
0 114
 
0.9%
Other values (16) 546
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69930
99.9%
Punctuation 60
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9725
13.9%
e 6235
 
8.9%
r 4804
 
6.9%
o 4543
 
6.5%
s 4027
 
5.8%
t 4027
 
5.8%
a 3919
 
5.6%
i 3665
 
5.2%
n 3396
 
4.9%
l 2482
 
3.5%
Other values (63) 23107
33.0%
Punctuation
ValueCountFrequency (%)
’ 34
56.7%
– 20
33.3%
” 3
 
5.0%
“ 3
 
5.0%

addtl_info2
Text

MISSING 

Distinct87
Distinct (%)38.0%
Missing206
Missing (%)47.4%
Memory size35.5 KiB
2023-12-09T22:17:40.884212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length302
Median length149
Mean length72.3231441
Min length19

Characters and Unicode

Total characters16562
Distinct characters43
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)24.9%

Sample

1st rowExtended Day Program, Student Summer Orientation, Summer Internship Program offered, Weekend Program offered
2nd rowStudent Summer Orientation, Weekend Program offered
3rd rowExtended Day Program
4th rowExtended Day Program Requirement
5th rowExtended Day Program
ValueCountFrequency (%)
program 252
12.9%
requirement 188
 
9.7%
summer 146
 
7.5%
extended 140
 
7.2%
day 138
 
7.1%
offered 136
 
7.0%
service 122
 
6.3%
community 122
 
6.3%
orientation 116
 
6.0%
student 116
 
6.0%
Other values (42) 470
24.2%
2023-12-09T22:17:41.301215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2279
13.8%
1731
 
10.5%
r 1490
 
9.0%
n 1103
 
6.7%
t 1050
 
6.3%
m 1008
 
6.1%
i 889
 
5.4%
o 828
 
5.0%
d 728
 
4.4%
u 676
 
4.1%
Other values (33) 4780
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12777
77.1%
Space Separator 1731
 
10.5%
Uppercase Letter 1679
 
10.1%
Other Punctuation 374
 
2.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2279
17.8%
r 1490
11.7%
n 1103
8.6%
t 1050
8.2%
m 1008
7.9%
i 889
 
7.0%
o 828
 
6.5%
d 728
 
5.7%
u 676
 
5.3%
a 618
 
4.8%
Other values (14) 2108
16.5%
Uppercase Letter
ValueCountFrequency (%)
S 391
23.3%
P 278
16.6%
R 216
12.9%
O 159
9.5%
D 153
 
9.1%
E 141
 
8.4%
C 138
 
8.2%
W 97
 
5.8%
I 70
 
4.2%
A 26
 
1.5%
Other values (3) 10
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 348
93.0%
; 23
 
6.1%
. 2
 
0.5%
: 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1731
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14456
87.3%
Common 2106
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2279
15.8%
r 1490
 
10.3%
n 1103
 
7.6%
t 1050
 
7.3%
m 1008
 
7.0%
i 889
 
6.1%
o 828
 
5.7%
d 728
 
5.0%
u 676
 
4.7%
a 618
 
4.3%
Other values (27) 3787
26.2%
Common
ValueCountFrequency (%)
1731
82.2%
, 348
 
16.5%
; 23
 
1.1%
. 2
 
0.1%
: 1
 
< 0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16562
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2279
13.8%
1731
 
10.5%
r 1490
 
9.0%
n 1103
 
6.7%
t 1050
 
6.3%
m 1008
 
6.1%
i 889
 
5.4%
o 828
 
5.0%
d 728
 
4.4%
u 676
 
4.1%
Other values (33) 4780
28.9%

start_time
Text

Distinct38
Distinct (%)8.8%
Missing4
Missing (%)0.9%
Memory size27.2 KiB
2023-12-09T22:17:41.504900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3017
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)4.9%

Sample

1st row7:45 AM
2nd row8:15 AM
3rd row8:00 AM
4th row8:00 AM
5th row8:00 AM
ValueCountFrequency (%)
am 431
50.0%
8:00 152
 
17.6%
8:30 75
 
8.7%
8:15 52
 
6.0%
8:45 33
 
3.8%
9:00 25
 
2.9%
7:45 12
 
1.4%
8:40 10
 
1.2%
8:25 9
 
1.0%
8:10 9
 
1.0%
Other values (29) 54
 
6.3%
2023-12-09T22:17:41.824092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 479
15.9%
: 431
14.3%
431
14.3%
A 431
14.3%
M 431
14.3%
8 374
12.4%
5 131
 
4.3%
3 92
 
3.0%
1 72
 
2.4%
4 58
 
1.9%
Other values (4) 87
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1293
42.9%
Uppercase Letter 862
28.6%
Other Punctuation 431
 
14.3%
Space Separator 431
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 479
37.0%
8 374
28.9%
5 131
 
10.1%
3 92
 
7.1%
1 72
 
5.6%
4 58
 
4.5%
9 34
 
2.6%
7 29
 
2.2%
2 23
 
1.8%
6 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
A 431
50.0%
M 431
50.0%
Other Punctuation
ValueCountFrequency (%)
: 431
100.0%
Space Separator
ValueCountFrequency (%)
431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2155
71.4%
Latin 862
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 479
22.2%
: 431
20.0%
431
20.0%
8 374
17.4%
5 131
 
6.1%
3 92
 
4.3%
1 72
 
3.3%
4 58
 
2.7%
9 34
 
1.6%
7 29
 
1.3%
Other values (2) 24
 
1.1%
Latin
ValueCountFrequency (%)
A 431
50.0%
M 431
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3017
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 479
15.9%
: 431
14.3%
431
14.3%
A 431
14.3%
M 431
14.3%
8 374
12.4%
5 131
 
4.3%
3 92
 
3.0%
1 72
 
2.4%
4 58
 
1.9%
Other values (4) 87
 
2.9%

end_time
Text

Distinct59
Distinct (%)13.7%
Missing4
Missing (%)0.9%
Memory size27.2 KiB
2023-12-09T22:17:42.058941image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3017
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)6.5%

Sample

1st row2:05 PM
2nd row3:00 PM
3rd row2:20 PM
4th row3:50 PM
5th row4:00 PM
ValueCountFrequency (%)
pm 431
50.0%
3:00 81
 
9.4%
3:30 63
 
7.3%
3:15 52
 
6.0%
3:45 35
 
4.1%
4:00 34
 
3.9%
2:45 26
 
3.0%
3:20 14
 
1.6%
2:30 13
 
1.5%
4:15 7
 
0.8%
Other values (50) 106
 
12.3%
2023-12-09T22:17:42.411362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 431
14.3%
431
14.3%
P 431
14.3%
M 431
14.3%
3 400
13.3%
0 380
12.6%
5 166
 
5.5%
4 135
 
4.5%
2 102
 
3.4%
1 82
 
2.7%
Other values (4) 28
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1293
42.9%
Uppercase Letter 862
28.6%
Other Punctuation 431
 
14.3%
Space Separator 431
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 400
30.9%
0 380
29.4%
5 166
12.8%
4 135
 
10.4%
2 102
 
7.9%
1 82
 
6.3%
7 13
 
1.0%
6 6
 
0.5%
9 5
 
0.4%
8 4
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
P 431
50.0%
M 431
50.0%
Other Punctuation
ValueCountFrequency (%)
: 431
100.0%
Space Separator
ValueCountFrequency (%)
431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2155
71.4%
Latin 862
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
: 431
20.0%
431
20.0%
3 400
18.6%
0 380
17.6%
5 166
 
7.7%
4 135
 
6.3%
2 102
 
4.7%
1 82
 
3.8%
7 13
 
0.6%
6 6
 
0.3%
Other values (2) 9
 
0.4%
Latin
ValueCountFrequency (%)
P 431
50.0%
M 431
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3017
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 431
14.3%
431
14.3%
P 431
14.3%
M 431
14.3%
3 400
13.3%
0 380
12.6%
5 166
 
5.5%
4 135
 
4.5%
2 102
 
3.4%
1 82
 
2.7%
Other values (4) 28
 
0.9%

se_services
Text

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
2023-12-09T22:17:42.637119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length102
Median length102
Mean length102
Min length102

Characters and Unicode

Total characters44370
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
2nd rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
3rd rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
4th rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
5th rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
ValueCountFrequency (%)
this 435
 
6.7%
school 435
 
6.7%
will 435
 
6.7%
provide 435
 
6.7%
students 435
 
6.7%
with 435
 
6.7%
disabilities 435
 
6.7%
the 435
 
6.7%
supports 435
 
6.7%
and 435
 
6.7%
Other values (5) 2175
33.3%
2023-12-09T22:17:42.974768image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6090
13.7%
i 5220
11.8%
s 4785
10.8%
e 3480
 
7.8%
t 3480
 
7.8%
d 2610
 
5.9%
o 2175
 
4.9%
h 2175
 
4.9%
l 1740
 
3.9%
n 1740
 
3.9%
Other values (13) 10875
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36105
81.4%
Space Separator 6090
 
13.7%
Uppercase Letter 1740
 
3.9%
Other Punctuation 435
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 5220
14.5%
s 4785
13.3%
e 3480
9.6%
t 3480
9.6%
d 2610
 
7.2%
o 2175
 
6.0%
h 2175
 
6.0%
l 1740
 
4.8%
n 1740
 
4.8%
r 1740
 
4.8%
Other values (7) 6960
19.3%
Uppercase Letter
ValueCountFrequency (%)
E 435
25.0%
P 435
25.0%
T 435
25.0%
I 435
25.0%
Space Separator
ValueCountFrequency (%)
6090
100.0%
Other Punctuation
ValueCountFrequency (%)
. 435
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37845
85.3%
Common 6525
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 5220
13.8%
s 4785
12.6%
e 3480
 
9.2%
t 3480
 
9.2%
d 2610
 
6.9%
o 2175
 
5.7%
h 2175
 
5.7%
l 1740
 
4.6%
n 1740
 
4.6%
r 1740
 
4.6%
Other values (11) 8700
23.0%
Common
ValueCountFrequency (%)
6090
93.3%
. 435
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6090
13.7%
i 5220
11.8%
s 4785
10.8%
e 3480
 
7.8%
t 3480
 
7.8%
d 2610
 
5.9%
o 2175
 
4.9%
h 2175
 
4.9%
l 1740
 
3.9%
n 1740
 
3.9%
Other values (13) 10875
24.5%

ell_programs
Text

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
2023-12-09T22:17:43.145025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length91
Median length3
Mean length7.468965517
Min length3

Characters and Unicode

Total characters3249
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st rowESL
2nd rowESL
3rd rowESL
4th rowESL
5th rowESL
ValueCountFrequency (%)
esl 435
68.8%
transitional 40
 
6.3%
bilingual 40
 
6.3%
program 40
 
6.3%
spanish 39
 
6.2%
chinese 15
 
2.4%
dual 8
 
1.3%
language 8
 
1.3%
haitian 2
 
0.3%
creole 2
 
0.3%
Other values (3) 3
 
0.5%
2023-12-09T22:17:43.434824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 474
14.6%
L 443
13.6%
E 435
13.4%
a 230
 
7.1%
i 221
 
6.8%
197
 
6.1%
n 186
 
5.7%
l 131
 
4.0%
r 123
 
3.8%
g 97
 
3.0%
Other values (21) 712
21.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1502
46.2%
Lowercase Letter 1443
44.4%
Space Separator 197
 
6.1%
Other Punctuation 107
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 230
15.9%
i 221
15.3%
n 186
12.9%
l 131
9.1%
r 123
8.5%
g 97
6.7%
s 96
6.7%
o 82
 
5.7%
u 57
 
4.0%
h 54
 
3.7%
Other values (6) 166
11.5%
Uppercase Letter
ValueCountFrequency (%)
S 474
31.6%
L 443
29.5%
E 435
29.0%
B 41
 
2.7%
T 40
 
2.7%
P 40
 
2.7%
C 17
 
1.1%
D 8
 
0.5%
H 2
 
0.1%
R 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
; 48
44.9%
: 48
44.9%
, 11
 
10.3%
Space Separator
ValueCountFrequency (%)
197
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2945
90.6%
Common 304
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 474
16.1%
L 443
15.0%
E 435
14.8%
a 230
7.8%
i 221
7.5%
n 186
 
6.3%
l 131
 
4.4%
r 123
 
4.2%
g 97
 
3.3%
s 96
 
3.3%
Other values (17) 509
17.3%
Common
ValueCountFrequency (%)
197
64.8%
; 48
 
15.8%
: 48
 
15.8%
, 11
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3249
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 474
14.6%
L 443
13.6%
E 435
13.4%
a 230
 
7.1%
i 221
 
6.8%
197
 
6.1%
n 186
 
5.7%
l 131
 
4.0%
r 123
 
3.8%
g 97
 
3.0%
Other values (21) 712
21.9%

school_accessibility_description
Text

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
2023-12-09T22:17:43.612393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length23
Mean length24.15862069
Min length23

Characters and Unicode

Total characters10509
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Functionally Accessible
2nd rowFunctionally Accessible
3rd rowNot Functionally Accessible
4th rowFunctionally Accessible
5th rowFunctionally Accessible
ValueCountFrequency (%)
functionally 435
43.7%
accessible 435
43.7%
not 126
 
12.7%
2023-12-09T22:17:43.926371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 1305
12.4%
l 1305
12.4%
n 870
 
8.3%
i 870
 
8.3%
e 870
 
8.3%
s 870
 
8.3%
t 561
 
5.3%
o 561
 
5.3%
561
 
5.3%
F 435
 
4.1%
Other values (6) 2301
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8952
85.2%
Uppercase Letter 996
 
9.5%
Space Separator 561
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 1305
14.6%
l 1305
14.6%
n 870
9.7%
i 870
9.7%
e 870
9.7%
s 870
9.7%
t 561
6.3%
o 561
6.3%
u 435
 
4.9%
a 435
 
4.9%
Other values (2) 870
9.7%
Uppercase Letter
ValueCountFrequency (%)
F 435
43.7%
A 435
43.7%
N 126
 
12.7%
Space Separator
ValueCountFrequency (%)
561
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9948
94.7%
Common 561
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 1305
13.1%
l 1305
13.1%
n 870
8.7%
i 870
8.7%
e 870
8.7%
s 870
8.7%
t 561
 
5.6%
o 561
 
5.6%
F 435
 
4.4%
u 435
 
4.4%
Other values (5) 1866
18.8%
Common
ValueCountFrequency (%)
561
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10509
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 1305
12.4%
l 1305
12.4%
n 870
 
8.3%
i 870
 
8.3%
e 870
 
8.3%
s 870
 
8.3%
t 561
 
5.3%
o 561
 
5.3%
561
 
5.3%
F 435
 
4.1%
Other values (6) 2301
21.9%

number_programs
Text

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
2023-12-09T22:17:44.053994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.002298851
Min length1

Characters and Unicode

Total characters436
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row6
ValueCountFrequency (%)
1 321
73.8%
2 47
 
10.8%
4 18
 
4.1%
3 18
 
4.1%
5 9
 
2.1%
6 8
 
1.8%
7 6
 
1.4%
8 6
 
1.4%
9 1
 
0.2%
10 1
 
0.2%
2023-12-09T22:17:44.295173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 322
73.9%
2 47
 
10.8%
4 18
 
4.1%
3 18
 
4.1%
5 9
 
2.1%
6 8
 
1.8%
7 6
 
1.4%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 436
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 322
73.9%
2 47
 
10.8%
4 18
 
4.1%
3 18
 
4.1%
5 9
 
2.1%
6 8
 
1.8%
7 6
 
1.4%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 436
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 322
73.9%
2 47
 
10.8%
4 18
 
4.1%
3 18
 
4.1%
5 9
 
2.1%
6 8
 
1.8%
7 6
 
1.4%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 436
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 322
73.9%
2 47
 
10.8%
4 18
 
4.1%
3 18
 
4.1%
5 9
 
2.1%
6 8
 
1.8%
7 6
 
1.4%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%

priority01
Text

Distinct76
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size51.4 KiB
2023-12-09T22:17:44.621209image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length298
Median length245
Mean length63.41149425
Min length17

Characters and Unicode

Total characters27584
Distinct characters68
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)11.5%

Sample

1st rowPriority to Queens students or residents who attend an information session
2nd rowPriority to New York City residents who attend an information session
3rd rowPriority to continuing 8th graders
4th rowPriority to Bronx students or residents who attend an information session
5th rowOpen to New York City residents
ValueCountFrequency (%)
to 447
 
10.1%
residents 339
 
7.7%
priority 316
 
7.2%
or 244
 
5.5%
students 223
 
5.1%
who 198
 
4.5%
an 173
 
3.9%
attend 173
 
3.9%
information 171
 
3.9%
session 170
 
3.9%
Other values (168) 1953
44.3%
2023-12-09T22:17:45.140043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3984
14.4%
t 2792
10.1%
n 2392
8.7%
o 2343
8.5%
e 2302
8.3%
i 2174
 
7.9%
r 2086
 
7.6%
s 1996
 
7.2%
a 1029
 
3.7%
d 977
 
3.5%
Other values (58) 5509
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21807
79.1%
Space Separator 3984
 
14.4%
Uppercase Letter 1552
 
5.6%
Decimal Number 155
 
0.6%
Other Punctuation 50
 
0.2%
Dash Punctuation 20
 
0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Initial Punctuation 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2792
12.8%
n 2392
11.0%
o 2343
10.7%
e 2302
10.6%
i 2174
10.0%
r 2086
9.6%
s 1996
9.2%
a 1029
 
4.7%
d 977
 
4.5%
y 593
 
2.7%
Other values (15) 3123
14.3%
Uppercase Letter
ValueCountFrequency (%)
P 320
20.6%
Y 178
11.5%
N 178
11.5%
C 164
10.6%
B 131
8.4%
O 122
 
7.9%
S 82
 
5.3%
L 74
 
4.8%
E 63
 
4.1%
D 41
 
2.6%
Other values (10) 199
12.8%
Decimal Number
ValueCountFrequency (%)
8 79
51.0%
1 19
 
12.3%
2 18
 
11.6%
6 9
 
5.8%
5 8
 
5.2%
3 8
 
5.2%
0 6
 
3.9%
4 4
 
2.6%
9 2
 
1.3%
7 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 26
52.0%
, 8
 
16.0%
/ 5
 
10.0%
; 5
 
10.0%
% 2
 
4.0%
& 2
 
4.0%
: 2
 
4.0%
Space Separator
ValueCountFrequency (%)
3984
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23359
84.7%
Common 4225
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2792
12.0%
n 2392
10.2%
o 2343
10.0%
e 2302
9.9%
i 2174
9.3%
r 2086
8.9%
s 1996
8.5%
a 1029
 
4.4%
d 977
 
4.2%
y 593
 
2.5%
Other values (35) 4675
20.0%
Common
ValueCountFrequency (%)
3984
94.3%
8 79
 
1.9%
. 26
 
0.6%
- 20
 
0.5%
1 19
 
0.4%
2 18
 
0.4%
6 9
 
0.2%
5 8
 
0.2%
3 8
 
0.2%
, 8
 
0.2%
Other values (13) 46
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27582
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3984
14.4%
t 2792
10.1%
n 2392
8.7%
o 2343
8.5%
e 2302
8.3%
i 2174
 
7.9%
r 2086
 
7.6%
s 1996
 
7.2%
a 1029
 
3.7%
d 977
 
3.5%
Other values (56) 5507
20.0%
Punctuation
ValueCountFrequency (%)
“ 1
50.0%
” 1
50.0%

priority02
Text

MISSING 

Distinct61
Distinct (%)17.3%
Missing83
Missing (%)19.1%
Memory size41.7 KiB
2023-12-09T22:17:45.417728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length330
Median length267
Mean length55.97727273
Min length1

Characters and Unicode

Total characters19704
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)13.1%

Sample

1st rowThen to New York City residents who attend an information session
2nd rowThen to New York City residents
3rd rowThen to Brooklyn students or residents who attend an information session
4th rowThen to New York City residents who attend an information session
5th rowAdmission is based on the outcome of a competitive audition and review of the student’s record
ValueCountFrequency (%)
to 378
11.1%
residents 336
 
9.9%
then 329
 
9.7%
new 246
 
7.2%
york 246
 
7.2%
city 246
 
7.2%
who 189
 
5.5%
an 169
 
5.0%
information 169
 
5.0%
attend 169
 
5.0%
Other values (144) 930
27.3%
2023-12-09T22:17:45.879759image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3063
15.5%
e 1923
9.8%
n 1896
9.6%
t 1890
9.6%
o 1645
8.3%
s 1502
 
7.6%
i 1306
 
6.6%
r 1083
 
5.5%
a 710
 
3.6%
d 704
 
3.6%
Other values (57) 3982
20.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15144
76.9%
Space Separator 3063
 
15.5%
Uppercase Letter 1313
 
6.7%
Decimal Number 108
 
0.5%
Other Punctuation 70
 
0.4%
Close Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1923
12.7%
n 1896
12.5%
t 1890
12.5%
o 1645
10.9%
s 1502
9.9%
i 1306
8.6%
r 1083
7.2%
a 710
 
4.7%
d 704
 
4.6%
h 599
 
4.0%
Other values (14) 1886
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 330
25.1%
C 251
19.1%
Y 246
18.7%
N 246
18.7%
B 45
 
3.4%
P 32
 
2.4%
D 25
 
1.9%
F 22
 
1.7%
M 21
 
1.6%
Q 20
 
1.5%
Other values (14) 75
 
5.7%
Decimal Number
ValueCountFrequency (%)
2 20
18.5%
1 19
17.6%
8 15
13.9%
5 13
12.0%
3 12
11.1%
6 10
9.3%
0 7
 
6.5%
9 5
 
4.6%
4 5
 
4.6%
7 2
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 29
41.4%
: 21
30.0%
, 16
22.9%
; 3
 
4.3%
& 1
 
1.4%
Space Separator
ValueCountFrequency (%)
3063
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16457
83.5%
Common 3247
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1923
11.7%
n 1896
11.5%
t 1890
11.5%
o 1645
10.0%
s 1502
9.1%
i 1306
7.9%
r 1083
 
6.6%
a 710
 
4.3%
d 704
 
4.3%
h 599
 
3.6%
Other values (38) 3199
19.4%
Common
ValueCountFrequency (%)
3063
94.3%
. 29
 
0.9%
: 21
 
0.6%
2 20
 
0.6%
1 19
 
0.6%
, 16
 
0.5%
8 15
 
0.5%
5 13
 
0.4%
3 12
 
0.4%
6 10
 
0.3%
Other values (9) 29
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19703
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3063
15.5%
e 1923
9.8%
n 1896
9.6%
t 1890
9.6%
o 1645
8.3%
s 1502
 
7.6%
i 1306
 
6.6%
r 1083
 
5.5%
a 710
 
3.6%
d 704
 
3.6%
Other values (56) 3981
20.2%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

priority03
Text

MISSING 

Distinct34
Distinct (%)14.0%
Missing192
Missing (%)44.1%
Memory size31.2 KiB
2023-12-09T22:17:46.176712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length369
Median length236
Mean length48.56790123
Min length1

Characters and Unicode

Total characters11802
Distinct characters65
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)8.6%

Sample

1st rowThen to Queens students or residents
2nd rowThen to New York City residents who attend an information session
3rd rowThen to Bronx students or residents
4th rowStudents must audition for each program (studio) to which they are applying
5th rowThen to New York City residents who attend an information session
ValueCountFrequency (%)
to 251
 
12.4%
residents 228
 
11.3%
then 224
 
11.1%
students 165
 
8.2%
or 142
 
7.0%
new 87
 
4.3%
york 87
 
4.3%
city 87
 
4.3%
who 63
 
3.1%
bronx 57
 
2.8%
Other values (99) 630
31.2%
2023-12-09T22:17:48.355836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1786
15.1%
e 1244
10.5%
t 1160
9.8%
n 1152
9.8%
s 992
8.4%
o 955
8.1%
r 742
 
6.3%
i 574
 
4.9%
d 502
 
4.3%
h 359
 
3.0%
Other values (55) 2336
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9135
77.4%
Space Separator 1786
 
15.1%
Uppercase Letter 758
 
6.4%
Other Punctuation 58
 
0.5%
Decimal Number 48
 
0.4%
Close Punctuation 10
 
0.1%
Open Punctuation 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1244
13.6%
t 1160
12.7%
n 1152
12.6%
s 992
10.9%
o 955
10.5%
r 742
8.1%
i 574
6.3%
d 502
5.5%
h 359
 
3.9%
a 325
 
3.6%
Other values (14) 1130
12.4%
Uppercase Letter
ValueCountFrequency (%)
T 225
29.7%
B 94
12.4%
C 92
12.1%
N 88
 
11.6%
Y 87
 
11.5%
Q 27
 
3.6%
F 27
 
3.6%
M 26
 
3.4%
P 17
 
2.2%
Z 15
 
2.0%
Other values (13) 60
 
7.9%
Decimal Number
ValueCountFrequency (%)
5 10
20.8%
0 9
18.8%
2 6
12.5%
1 6
12.5%
4 5
10.4%
9 3
 
6.2%
6 3
 
6.2%
3 3
 
6.2%
8 2
 
4.2%
7 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
: 25
43.1%
. 20
34.5%
; 7
 
12.1%
% 4
 
6.9%
, 2
 
3.4%
Space Separator
ValueCountFrequency (%)
1786
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9893
83.8%
Common 1909
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1244
12.6%
t 1160
11.7%
n 1152
11.6%
s 992
10.0%
o 955
9.7%
r 742
 
7.5%
i 574
 
5.8%
d 502
 
5.1%
h 359
 
3.6%
a 325
 
3.3%
Other values (37) 1888
19.1%
Common
ValueCountFrequency (%)
1786
93.6%
: 25
 
1.3%
. 20
 
1.0%
5 10
 
0.5%
) 10
 
0.5%
0 9
 
0.5%
( 7
 
0.4%
; 7
 
0.4%
2 6
 
0.3%
1 6
 
0.3%
Other values (8) 23
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11802
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1786
15.1%
e 1244
10.5%
t 1160
9.8%
n 1152
9.8%
s 992
8.4%
o 955
8.1%
r 742
 
6.3%
i 574
 
4.9%
d 502
 
4.3%
h 359
 
3.0%
Other values (55) 2336
19.8%

priority04
Text

MISSING 

Distinct27
Distinct (%)15.3%
Missing258
Missing (%)59.3%
Memory size24.3 KiB
2023-12-09T22:17:48.621743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length300
Median length31
Mean length36.2259887
Min length1

Characters and Unicode

Total characters6412
Distinct characters58
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)9.6%

Sample

1st rowThen to New York City residents
2nd rowThen to Brooklyn students or residents
3rd rowThen to New York City residents
4th rowStudents must be residents of New York City at the time of audition
5th rowThen to Districts 1 and 2 students or residents
ValueCountFrequency (%)
to 175
14.6%
then 170
14.2%
residents 168
14.0%
new 136
11.4%
york 136
11.4%
city 136
11.4%
students 40
 
3.3%
or 33
 
2.8%
bronx 14
 
1.2%
who 13
 
1.1%
Other values (71) 175
14.6%
2023-12-09T22:17:49.040083image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1027
16.0%
e 754
11.8%
t 630
9.8%
n 484
 
7.5%
s 472
 
7.4%
o 440
 
6.9%
r 401
 
6.3%
i 378
 
5.9%
d 238
 
3.7%
h 207
 
3.2%
Other values (48) 1381
21.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4694
73.2%
Space Separator 1027
 
16.0%
Uppercase Letter 639
 
10.0%
Decimal Number 36
 
0.6%
Other Punctuation 15
 
0.2%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 754
16.1%
t 630
13.4%
n 484
10.3%
s 472
10.1%
o 440
9.4%
r 401
8.5%
i 378
8.1%
d 238
 
5.1%
h 207
 
4.4%
w 154
 
3.3%
Other values (14) 536
11.4%
Uppercase Letter
ValueCountFrequency (%)
T 170
26.6%
C 136
21.3%
Y 136
21.3%
N 136
21.3%
B 18
 
2.8%
D 10
 
1.6%
S 6
 
0.9%
F 6
 
0.9%
M 5
 
0.8%
P 3
 
0.5%
Other values (9) 13
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 7
19.4%
0 6
16.7%
6 5
13.9%
3 5
13.9%
1 5
13.9%
5 4
11.1%
7 1
 
2.8%
9 1
 
2.8%
8 1
 
2.8%
4 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 6
40.0%
: 5
33.3%
, 4
26.7%
Space Separator
ValueCountFrequency (%)
1027
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5333
83.2%
Common 1079
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 754
14.1%
t 630
11.8%
n 484
9.1%
s 472
8.9%
o 440
 
8.3%
r 401
 
7.5%
i 378
 
7.1%
d 238
 
4.5%
h 207
 
3.9%
T 170
 
3.2%
Other values (33) 1159
21.7%
Common
ValueCountFrequency (%)
1027
95.2%
2 7
 
0.6%
0 6
 
0.6%
. 6
 
0.6%
6 5
 
0.5%
: 5
 
0.5%
3 5
 
0.5%
1 5
 
0.5%
5 4
 
0.4%
, 4
 
0.4%
Other values (5) 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1027
16.0%
e 754
11.8%
t 630
9.8%
n 484
 
7.5%
s 472
 
7.4%
o 440
 
6.9%
r 401
 
6.3%
i 378
 
5.9%
d 238
 
3.7%
h 207
 
3.2%
Other values (48) 1381
21.5%

priority05
Text

MISSING 

Distinct9
Distinct (%)23.1%
Missing396
Missing (%)91.0%
Memory size16.0 KiB
2023-12-09T22:17:49.254086image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length31
Mean length34.35897436
Min length31

Characters and Unicode

Total characters1340
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)12.8%

Sample

1st rowThen to New York City residents
2nd rowThen to Manhattan students or residents
3rd rowThen to Brooklyn students or residents
4th rowThen to New York City residents
5th rowThen to District 27 students or residents
ValueCountFrequency (%)
then 39
16.2%
residents 39
16.2%
to 39
16.2%
new 23
9.5%
york 23
9.5%
city 23
9.5%
students 16
6.6%
or 16
6.6%
brooklyn 7
 
2.9%
manhattan 3
 
1.2%
Other values (11) 13
 
5.4%
2023-12-09T22:17:49.587460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
15.1%
e 160
11.9%
t 145
10.8%
s 116
8.7%
n 111
8.3%
o 93
 
6.9%
r 89
 
6.6%
i 68
 
5.1%
d 57
 
4.3%
h 42
 
3.1%
Other values (23) 257
19.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1003
74.9%
Space Separator 202
 
15.1%
Uppercase Letter 124
 
9.3%
Decimal Number 9
 
0.7%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 160
16.0%
t 145
14.5%
s 116
11.6%
n 111
11.1%
o 93
9.3%
r 89
8.9%
i 68
6.8%
d 57
 
5.7%
h 42
 
4.2%
k 30
 
3.0%
Other values (7) 92
9.2%
Uppercase Letter
ValueCountFrequency (%)
T 39
31.5%
Y 23
18.5%
N 23
18.5%
C 23
18.5%
B 8
 
6.5%
M 3
 
2.4%
D 3
 
2.4%
Q 2
 
1.6%
Decimal Number
ValueCountFrequency (%)
2 4
44.4%
3 2
22.2%
4 1
 
11.1%
7 1
 
11.1%
0 1
 
11.1%
Space Separator
ValueCountFrequency (%)
202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1127
84.1%
Common 213
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 160
14.2%
t 145
12.9%
s 116
10.3%
n 111
9.8%
o 93
8.3%
r 89
7.9%
i 68
 
6.0%
d 57
 
5.1%
h 42
 
3.7%
T 39
 
3.5%
Other values (15) 207
18.4%
Common
ValueCountFrequency (%)
202
94.8%
2 4
 
1.9%
3 2
 
0.9%
) 1
 
0.5%
4 1
 
0.5%
, 1
 
0.5%
7 1
 
0.5%
0 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
15.1%
e 160
11.9%
t 145
10.8%
s 116
8.7%
n 111
8.3%
o 93
 
6.9%
r 89
 
6.6%
i 68
 
5.1%
d 57
 
4.3%
h 42
 
3.1%
Other values (23) 257
19.2%

priority06
Text

MISSING 

Distinct5
Distinct (%)29.4%
Missing418
Missing (%)96.1%
Memory size14.7 KiB
2023-12-09T22:17:49.784299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length31
Mean length31.35294118
Min length17

Characters and Unicode

Total characters533
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)23.5%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to Queens students or residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 16
16.0%
to 16
16.0%
residents 16
16.0%
new 13
13.0%
york 13
13.0%
city 13
13.0%
students 3
 
3.0%
or 3
 
3.0%
brooklyn 1
 
1.0%
queens 1
 
1.0%
Other values (5) 5
 
5.0%
2023-12-09T22:17:50.134057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
15.6%
e 66
12.4%
t 53
9.9%
n 40
 
7.5%
s 39
 
7.3%
o 36
 
6.8%
r 34
 
6.4%
i 29
 
5.4%
d 19
 
3.6%
h 17
 
3.2%
Other values (18) 117
22.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 384
72.0%
Space Separator 83
 
15.6%
Uppercase Letter 61
 
11.4%
Decimal Number 3
 
0.6%
Other Punctuation 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 66
17.2%
t 53
13.8%
n 40
10.4%
s 39
10.2%
o 36
9.4%
r 34
8.9%
i 29
7.6%
d 19
 
4.9%
h 17
 
4.4%
y 15
 
3.9%
Other values (5) 36
9.4%
Uppercase Letter
ValueCountFrequency (%)
T 16
26.2%
Y 14
23.0%
C 13
21.3%
N 13
21.3%
B 2
 
3.3%
Q 1
 
1.6%
M 1
 
1.6%
F 1
 
1.6%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
7 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
: 1
50.0%
Space Separator
ValueCountFrequency (%)
83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 445
83.5%
Common 88
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 66
14.8%
t 53
11.9%
n 40
9.0%
s 39
8.8%
o 36
 
8.1%
r 34
 
7.6%
i 29
 
6.5%
d 19
 
4.3%
h 17
 
3.8%
T 16
 
3.6%
Other values (13) 96
21.6%
Common
ValueCountFrequency (%)
83
94.3%
2 2
 
2.3%
. 1
 
1.1%
7 1
 
1.1%
: 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 533
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
15.6%
e 66
12.4%
t 53
9.9%
n 40
 
7.5%
s 39
 
7.3%
o 36
 
6.8%
r 34
 
6.4%
i 29
 
5.4%
d 19
 
3.6%
h 17
 
3.2%
Other values (18) 117
22.0%

priority07
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing431
Missing (%)99.1%
Memory size13.9 KiB
2023-12-09T22:17:50.335136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length31
Mean length32.5
Min length31

Characters and Unicode

Total characters130
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowa) Priority to continuing 8th graders
ValueCountFrequency (%)
to 4
16.7%
then 3
12.5%
new 3
12.5%
york 3
12.5%
city 3
12.5%
residents 3
12.5%
a 1
 
4.2%
priority 1
 
4.2%
continuing 1
 
4.2%
8th 1
 
4.2%
2023-12-09T22:17:50.661941image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
15.4%
e 13
10.0%
t 13
10.0%
r 10
 
7.7%
i 10
 
7.7%
n 9
 
6.9%
o 9
 
6.9%
s 7
 
5.4%
h 4
 
3.1%
d 4
 
3.1%
Other values (14) 31
23.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 95
73.1%
Space Separator 20
 
15.4%
Uppercase Letter 13
 
10.0%
Close Punctuation 1
 
0.8%
Decimal Number 1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13
13.7%
t 13
13.7%
r 10
10.5%
i 10
10.5%
n 9
9.5%
o 9
9.5%
s 7
7.4%
h 4
 
4.2%
d 4
 
4.2%
y 4
 
4.2%
Other values (6) 12
12.6%
Uppercase Letter
ValueCountFrequency (%)
T 3
23.1%
C 3
23.1%
Y 3
23.1%
N 3
23.1%
P 1
 
7.7%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 108
83.1%
Common 22
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13
12.0%
t 13
12.0%
r 10
 
9.3%
i 10
 
9.3%
n 9
 
8.3%
o 9
 
8.3%
s 7
 
6.5%
h 4
 
3.7%
d 4
 
3.7%
y 4
 
3.7%
Other values (11) 25
23.1%
Common
ValueCountFrequency (%)
20
90.9%
) 1
 
4.5%
8 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
15.4%
e 13
10.0%
t 13
10.0%
r 10
 
7.7%
i 10
 
7.7%
n 9
 
6.9%
o 9
 
6.9%
s 7
 
5.4%
h 4
 
3.1%
d 4
 
3.1%
Other values (14) 31
23.8%

priority08
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing434
Missing (%)99.8%
Memory size13.8 KiB
2023-12-09T22:17:50.870661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters72
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowb) Then to Bronx students or residents who attend an information session
ValueCountFrequency (%)
b 1
8.3%
then 1
8.3%
to 1
8.3%
bronx 1
8.3%
students 1
8.3%
or 1
8.3%
residents 1
8.3%
who 1
8.3%
attend 1
8.3%
an 1
8.3%
Other values (2) 2
16.7%
2023-12-09T22:17:51.202908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
15.3%
n 9
12.5%
t 7
9.7%
o 7
9.7%
s 7
9.7%
e 6
8.3%
r 4
 
5.6%
i 4
 
5.6%
d 3
 
4.2%
a 3
 
4.2%
Other values (10) 11
15.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 58
80.6%
Space Separator 11
 
15.3%
Uppercase Letter 2
 
2.8%
Close Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 9
15.5%
t 7
12.1%
o 7
12.1%
s 7
12.1%
e 6
10.3%
r 4
6.9%
i 4
6.9%
d 3
 
5.2%
a 3
 
5.2%
h 2
 
3.4%
Other values (6) 6
10.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60
83.3%
Common 12
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 9
15.0%
t 7
11.7%
o 7
11.7%
s 7
11.7%
e 6
10.0%
r 4
6.7%
i 4
6.7%
d 3
 
5.0%
a 3
 
5.0%
h 2
 
3.3%
Other values (8) 8
13.3%
Common
ValueCountFrequency (%)
11
91.7%
) 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
15.3%
n 9
12.5%
t 7
9.7%
o 7
9.7%
s 7
9.7%
e 6
8.3%
r 4
 
5.6%
i 4
 
5.6%
d 3
 
4.2%
a 3
 
4.2%
Other values (10) 11
15.3%

priority09
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing434
Missing (%)99.8%
Memory size13.8 KiB
2023-12-09T22:17:51.426450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length68
Median length68
Mean length68
Min length68

Characters and Unicode

Total characters68
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowc) Then to New York City residents who attend an information session
ValueCountFrequency (%)
c 1
8.3%
then 1
8.3%
to 1
8.3%
new 1
8.3%
york 1
8.3%
city 1
8.3%
residents 1
8.3%
who 1
8.3%
attend 1
8.3%
an 1
8.3%
Other values (2) 2
16.7%
2023-12-09T22:17:51.770545image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
16.2%
n 7
10.3%
e 6
8.8%
t 6
8.8%
o 6
8.8%
i 5
 
7.4%
s 5
 
7.4%
a 3
 
4.4%
r 3
 
4.4%
h 2
 
2.9%
Other values (12) 14
20.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 52
76.5%
Space Separator 11
 
16.2%
Uppercase Letter 4
 
5.9%
Close Punctuation 1
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 7
13.5%
e 6
11.5%
t 6
11.5%
o 6
11.5%
i 5
9.6%
s 5
9.6%
a 3
5.8%
r 3
5.8%
h 2
 
3.8%
w 2
 
3.8%
Other values (6) 7
13.5%
Uppercase Letter
ValueCountFrequency (%)
Y 1
25.0%
C 1
25.0%
N 1
25.0%
T 1
25.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 56
82.4%
Common 12
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 7
12.5%
e 6
10.7%
t 6
10.7%
o 6
10.7%
i 5
8.9%
s 5
8.9%
a 3
 
5.4%
r 3
 
5.4%
h 2
 
3.6%
w 2
 
3.6%
Other values (10) 11
19.6%
Common
ValueCountFrequency (%)
11
91.7%
) 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
16.2%
n 7
10.3%
e 6
8.8%
t 6
8.8%
o 6
8.8%
i 5
 
7.4%
s 5
 
7.4%
a 3
 
4.4%
r 3
 
4.4%
h 2
 
2.9%
Other values (12) 14
20.6%

priority10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing434
Missing (%)99.8%
Memory size13.8 KiB
2023-12-09T22:17:52.031857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

Total characters74
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowd) Then to Bronx students or residents, e) Then to New York City residents
ValueCountFrequency (%)
then 2
14.3%
to 2
14.3%
residents 2
14.3%
d 1
7.1%
bronx 1
7.1%
students 1
7.1%
or 1
7.1%
e 1
7.1%
new 1
7.1%
york 1
7.1%
2023-12-09T22:17:52.359494image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
17.6%
e 9
12.2%
t 7
9.5%
n 6
8.1%
s 6
8.1%
o 5
 
6.8%
r 5
 
6.8%
d 4
 
5.4%
i 3
 
4.1%
T 2
 
2.7%
Other values (12) 14
18.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 52
70.3%
Space Separator 13
 
17.6%
Uppercase Letter 6
 
8.1%
Close Punctuation 2
 
2.7%
Other Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 9
17.3%
t 7
13.5%
n 6
11.5%
s 6
11.5%
o 5
9.6%
r 5
9.6%
d 4
7.7%
i 3
 
5.8%
h 2
 
3.8%
w 1
 
1.9%
Other values (4) 4
7.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
33.3%
C 1
16.7%
Y 1
16.7%
N 1
16.7%
B 1
16.7%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 58
78.4%
Common 16
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 9
15.5%
t 7
12.1%
n 6
10.3%
s 6
10.3%
o 5
8.6%
r 5
8.6%
d 4
6.9%
i 3
 
5.2%
T 2
 
3.4%
h 2
 
3.4%
Other values (9) 9
15.5%
Common
ValueCountFrequency (%)
13
81.2%
) 2
 
12.5%
, 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
17.6%
e 9
12.2%
t 7
9.5%
n 6
8.1%
s 6
8.1%
o 5
 
6.8%
r 5
 
6.8%
d 4
 
5.4%
i 3
 
4.1%
T 2
 
2.7%
Other values (12) 14
18.9%

location_1
Text

Distinct259
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Memory size53.2 KiB
2023-12-09T22:17:52.843709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length79
Mean length67.86436782
Min length59

Characters and Unicode

Total characters29521
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)41.1%

Sample

1st row8 21 Bay 25 Street Far Rockaway, NY 11691 (40.601989336, -73.762834323)
2nd row2630 Benson Avenue Brooklyn, NY 11214 (40.593593811, -73.984729232)
3rd row1014 Lafayette Avenue Brooklyn, NY 11221 (40.692133704, -73.931503172)
4th row1980 Lafayette Avenue Bronx, NY 10473 (40.822303765, -73.85596139)
5th row100 Amsterdam Avenue New York, NY 10023 (40.773670507, -73.985268558)
ValueCountFrequency (%)
ny 435
 
11.2%
avenue 187
 
4.8%
street 163
 
4.2%
brooklyn 121
 
3.1%
bronx 118
 
3.0%
new 105
 
2.7%
york 104
 
2.7%
east 55
 
1.4%
west 47
 
1.2%
road 27
 
0.7%
Other values (1103) 2519
64.9%
2023-12-09T22:17:53.542416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2612
 
8.8%
0 1904
 
6.4%
1 1896
 
6.4%
4 1524
 
5.2%
7 1488
 
5.0%
3 1443
 
4.9%
2 1126
 
3.8%
e 1125
 
3.8%
8 1109
 
3.8%
9 1077
 
3.6%
Other values (57) 14217
48.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13535
45.8%
Lowercase Letter 7051
23.9%
Space Separator 2612
 
8.8%
Uppercase Letter 2407
 
8.2%
Other Punctuation 1741
 
5.9%
Control 870
 
2.9%
Close Punctuation 435
 
1.5%
Dash Punctuation 435
 
1.5%
Open Punctuation 435
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 548
22.8%
Y 539
22.4%
B 307
12.8%
A 227
9.4%
S 207
 
8.6%
E 69
 
2.9%
R 56
 
2.3%
T 55
 
2.3%
W 55
 
2.3%
P 43
 
1.8%
Other values (15) 301
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 1125
16.0%
o 746
10.6%
r 733
10.4%
n 719
10.2%
t 633
9.0%
a 457
 
6.5%
l 316
 
4.5%
s 289
 
4.1%
u 266
 
3.8%
k 262
 
3.7%
Other values (14) 1505
21.3%
Decimal Number
ValueCountFrequency (%)
0 1904
14.1%
1 1896
14.0%
4 1524
11.3%
7 1488
11.0%
3 1443
10.7%
2 1126
8.3%
8 1109
8.2%
9 1077
8.0%
5 984
7.3%
6 984
7.3%
Other Punctuation
ValueCountFrequency (%)
. 870
50.0%
, 870
50.0%
' 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2612
100.0%
Control
ValueCountFrequency (%)
870
100.0%
Close Punctuation
ValueCountFrequency (%)
) 435
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 435
100.0%
Open Punctuation
ValueCountFrequency (%)
( 435
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20063
68.0%
Latin 9458
32.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1125
 
11.9%
o 746
 
7.9%
r 733
 
7.8%
n 719
 
7.6%
t 633
 
6.7%
N 548
 
5.8%
Y 539
 
5.7%
a 457
 
4.8%
l 316
 
3.3%
B 307
 
3.2%
Other values (39) 3335
35.3%
Common
ValueCountFrequency (%)
2612
13.0%
0 1904
 
9.5%
1 1896
 
9.5%
4 1524
 
7.6%
7 1488
 
7.4%
3 1443
 
7.2%
2 1126
 
5.6%
8 1109
 
5.5%
9 1077
 
5.4%
5 984
 
4.9%
Other values (8) 4900
24.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29521
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2612
 
8.8%
0 1904
 
6.4%
1 1896
 
6.4%
4 1524
 
5.2%
7 1488
 
5.0%
3 1443
 
4.9%
2 1126
 
3.8%
e 1125
 
3.8%
8 1109
 
3.8%
9 1077
 
3.6%
Other values (57) 14217
48.2%

community_board
Text

Distinct18
Distinct (%)4.2%
Missing3
Missing (%)0.7%
Memory size24.8 KiB
2023-12-09T22:17:53.749219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.270833333
Min length1

Characters and Unicode

Total characters549
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row14
2nd row13
3rd row3
4th row9
5th row7
ValueCountFrequency (%)
1 47
10.9%
4 43
10.0%
3 41
9.5%
2 37
8.6%
9 33
 
7.6%
6 32
 
7.4%
12 31
 
7.2%
8 28
 
6.5%
7 27
 
6.2%
5 27
 
6.2%
Other values (8) 86
19.9%
2023-12-09T22:17:54.098588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 184
33.5%
2 68
 
12.4%
4 57
 
10.4%
3 57
 
10.4%
6 36
 
6.6%
8 35
 
6.4%
9 33
 
6.0%
7 31
 
5.6%
5 30
 
5.5%
0 18
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 549
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 184
33.5%
2 68
 
12.4%
4 57
 
10.4%
3 57
 
10.4%
6 36
 
6.6%
8 35
 
6.4%
9 33
 
6.0%
7 31
 
5.6%
5 30
 
5.5%
0 18
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 549
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 184
33.5%
2 68
 
12.4%
4 57
 
10.4%
3 57
 
10.4%
6 36
 
6.6%
8 35
 
6.4%
9 33
 
6.0%
7 31
 
5.6%
5 30
 
5.5%
0 18
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 184
33.5%
2 68
 
12.4%
4 57
 
10.4%
3 57
 
10.4%
6 36
 
6.6%
8 35
 
6.4%
9 33
 
6.0%
7 31
 
5.6%
5 30
 
5.5%
0 18
 
3.3%

council_district
Text

Distinct51
Distinct (%)11.8%
Missing3
Missing (%)0.7%
Memory size25.0 KiB
2023-12-09T22:17:54.389999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.761574074
Min length1

Characters and Unicode

Total characters761
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row31
2nd row47
3rd row36
4th row18
5th row6
ValueCountFrequency (%)
3 23
 
5.3%
33 21
 
4.9%
17 20
 
4.6%
16 20
 
4.6%
1 18
 
4.2%
2 16
 
3.7%
26 16
 
3.7%
8 15
 
3.5%
15 14
 
3.2%
18 14
 
3.2%
Other values (41) 255
59.0%
2023-12-09T22:17:54.807738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 168
22.1%
3 146
19.2%
2 106
13.9%
4 87
11.4%
6 62
 
8.1%
7 53
 
7.0%
5 44
 
5.8%
8 40
 
5.3%
0 33
 
4.3%
9 22
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 761
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 168
22.1%
3 146
19.2%
2 106
13.9%
4 87
11.4%
6 62
 
8.1%
7 53
 
7.0%
5 44
 
5.8%
8 40
 
5.3%
0 33
 
4.3%
9 22
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 761
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 168
22.1%
3 146
19.2%
2 106
13.9%
4 87
11.4%
6 62
 
8.1%
7 53
 
7.0%
5 44
 
5.8%
8 40
 
5.3%
0 33
 
4.3%
9 22
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 761
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 168
22.1%
3 146
19.2%
2 106
13.9%
4 87
11.4%
6 62
 
8.1%
7 53
 
7.0%
5 44
 
5.8%
8 40
 
5.3%
0 33
 
4.3%
9 22
 
2.9%

census_tract
Text

Distinct201
Distinct (%)46.5%
Missing3
Missing (%)0.7%
Memory size25.5 KiB
2023-12-09T22:17:55.359015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.974537037
Min length1

Characters and Unicode

Total characters1285
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)25.2%

Sample

1st row100802
2nd row306
3rd row291
4th row16
5th row151
ValueCountFrequency (%)
409 10
 
2.3%
135 9
 
2.1%
151 8
 
1.9%
56 7
 
1.6%
194 7
 
1.6%
16 7
 
1.6%
225 6
 
1.4%
179 6
 
1.4%
89 6
 
1.4%
387 6
 
1.4%
Other values (191) 360
83.3%
2023-12-09T22:17:56.062630image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 263
20.5%
3 152
11.8%
2 133
10.4%
0 127
9.9%
5 123
9.6%
9 116
9.0%
4 107
8.3%
7 97
 
7.5%
6 85
 
6.6%
8 82
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1285
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 263
20.5%
3 152
11.8%
2 133
10.4%
0 127
9.9%
5 123
9.6%
9 116
9.0%
4 107
8.3%
7 97
 
7.5%
6 85
 
6.6%
8 82
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1285
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 263
20.5%
3 152
11.8%
2 133
10.4%
0 127
9.9%
5 123
9.6%
9 116
9.0%
4 107
8.3%
7 97
 
7.5%
6 85
 
6.6%
8 82
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1285
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 263
20.5%
3 152
11.8%
2 133
10.4%
0 127
9.9%
5 123
9.6%
9 116
9.0%
4 107
8.3%
7 97
 
7.5%
6 85
 
6.6%
8 82
 
6.4%

bin
Text

Distinct253
Distinct (%)58.7%
Missing4
Missing (%)0.9%
Memory size27.2 KiB
2023-12-09T22:17:56.520486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3017
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)39.9%

Sample

1st row4300730
2nd row3186454
3rd row3393805
4th row2022205
5th row1030341
ValueCountFrequency (%)
1030343 6
 
1.4%
2011810 6
 
1.4%
2007806 6
 
1.4%
2057045 6
 
1.4%
2074045 6
 
1.4%
2022205 6
 
1.4%
3336215 5
 
1.2%
1083802 5
 
1.2%
1017828 5
 
1.2%
3090738 5
 
1.2%
Other values (243) 375
87.0%
2023-12-09T22:17:57.081045image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 584
19.4%
1 381
12.6%
3 377
12.5%
2 346
11.5%
4 318
10.5%
5 239
7.9%
8 215
 
7.1%
7 201
 
6.7%
6 199
 
6.6%
9 157
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3017
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 584
19.4%
1 381
12.6%
3 377
12.5%
2 346
11.5%
4 318
10.5%
5 239
7.9%
8 215
 
7.1%
7 201
 
6.7%
6 199
 
6.6%
9 157
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3017
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 584
19.4%
1 381
12.6%
3 377
12.5%
2 346
11.5%
4 318
10.5%
5 239
7.9%
8 215
 
7.1%
7 201
 
6.7%
6 199
 
6.6%
9 157
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3017
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 584
19.4%
1 381
12.6%
3 377
12.5%
2 346
11.5%
4 318
10.5%
5 239
7.9%
8 215
 
7.1%
7 201
 
6.7%
6 199
 
6.6%
9 157
 
5.2%

bbl
Text

Distinct251
Distinct (%)58.2%
Missing4
Missing (%)0.9%
Memory size28.5 KiB
2023-12-09T22:17:57.395344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4310
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)39.2%

Sample

1st row4157360001
2nd row3068830001
3rd row3016160001
4th row2036040039
5th row1011560030
ValueCountFrequency (%)
2046330040 6
 
1.4%
2036040039 6
 
1.4%
2030590001 6
 
1.4%
1011570025 6
 
1.4%
2028170002 6
 
1.4%
2053680001 6
 
1.4%
2032470070 5
 
1.2%
3051030010 5
 
1.2%
1008720057 5
 
1.2%
3068830001 5
 
1.2%
Other values (241) 375
87.0%
2023-12-09T22:17:57.821668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1757
40.8%
1 616
 
14.3%
2 403
 
9.4%
3 375
 
8.7%
4 293
 
6.8%
5 200
 
4.6%
8 183
 
4.2%
6 171
 
4.0%
7 162
 
3.8%
9 150
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4310
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1757
40.8%
1 616
 
14.3%
2 403
 
9.4%
3 375
 
8.7%
4 293
 
6.8%
5 200
 
4.6%
8 183
 
4.2%
6 171
 
4.0%
7 162
 
3.8%
9 150
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1757
40.8%
1 616
 
14.3%
2 403
 
9.4%
3 375
 
8.7%
4 293
 
6.8%
5 200
 
4.6%
8 183
 
4.2%
6 171
 
4.0%
7 162
 
3.8%
9 150
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1757
40.8%
1 616
 
14.3%
2 403
 
9.4%
3 375
 
8.7%
4 293
 
6.8%
5 200
 
4.6%
8 183
 
4.2%
6 171
 
4.0%
7 162
 
3.8%
9 150
 
3.5%

nta
Text

Distinct118
Distinct (%)27.3%
Missing3
Missing (%)0.7%
Memory size55.9 KiB
2023-12-09T22:17:58.146920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters32400
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)7.9%

Sample

1st rowFar Rockaway-Bayswater
2nd rowGravesend
3rd rowStuyvesant Heights
4th rowSoundview-Castle Hill-Clason Point-Harding Park
5th rowLincoln Square
ValueCountFrequency (%)
east 42
 
4.2%
park 36
 
3.6%
north 34
 
3.4%
heights 28
 
2.8%
village 27
 
2.7%
hill 25
 
2.5%
south 25
 
2.5%
west 20
 
2.0%
square 19
 
1.9%
hills 15
 
1.5%
Other values (164) 730
72.9%
2023-12-09T22:17:58.602283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23837
73.6%
e 702
 
2.2%
a 639
 
2.0%
o 632
 
2.0%
r 599
 
1.8%
n 587
 
1.8%
l 553
 
1.7%
t 541
 
1.7%
i 520
 
1.6%
s 439
 
1.4%
Other values (45) 3351
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 23837
73.6%
Lowercase Letter 6883
 
21.2%
Uppercase Letter 1354
 
4.2%
Dash Punctuation 312
 
1.0%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 702
10.2%
a 639
9.3%
o 632
9.2%
r 599
8.7%
n 587
8.5%
l 553
 
8.0%
t 541
 
7.9%
i 520
 
7.6%
s 439
 
6.4%
h 235
 
3.4%
Other values (15) 1436
20.9%
Uppercase Letter
ValueCountFrequency (%)
H 183
13.5%
C 155
11.4%
B 151
11.2%
S 119
 
8.8%
M 90
 
6.6%
P 89
 
6.6%
E 63
 
4.7%
N 60
 
4.4%
W 57
 
4.2%
V 55
 
4.1%
Other values (14) 332
24.5%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
' 1
 
25.0%
Space Separator
ValueCountFrequency (%)
23837
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24163
74.6%
Latin 8237
 
25.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 702
 
8.5%
a 639
 
7.8%
o 632
 
7.7%
r 599
 
7.3%
n 587
 
7.1%
l 553
 
6.7%
t 541
 
6.6%
i 520
 
6.3%
s 439
 
5.3%
h 235
 
2.9%
Other values (39) 2790
33.9%
Common
ValueCountFrequency (%)
23837
98.7%
- 312
 
1.3%
( 5
 
< 0.1%
) 5
 
< 0.1%
. 3
 
< 0.1%
' 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23837
73.6%
e 702
 
2.2%
a 639
 
2.0%
o 632
 
2.0%
r 599
 
1.8%
n 587
 
1.8%
l 553
 
1.7%
t 541
 
1.7%
i 520
 
1.6%
s 439
 
1.4%
Other values (45) 3351
 
10.3%